Publications

2020 [ to top ]

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  Anomaly Detection in Beehives using Deep Recurrent Autoencoders. Davidson, Padraig; Steininger, Michael; Lautenschlager, Florian; Kobs, Konstantin; Krause, Anna; Hotho, Andreas (2020). 142-149.
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  @inproceedings{davidson2020anomaly, author = {Davidson, Padraig and Steininger, Michael and Lautenschlager, Florian and Kobs, Konstantin and Krause, Anna and Hotho, Andreas}, booktitle = {Proceedings of the 9th International Conference on Sensor Networks (SENSORNETS 2020)}, keywords = {anomaly-detection autoencoder beehive myown rnn sensor-network from:pdavidson}, number = 9, pages = {142-149}, publisher = {SCITEPRESS – Science and Technology Publications, Lda.}, title = {Anomaly Detection in Beehives using Deep Recurrent Autoencoders}, year = 2020 }
  %0 Conference Paper %1 davidson2020anomaly %A Davidson, Padraig %A Steininger, Michael %A Lautenschlager, Florian %A Kobs, Konstantin %A Krause, Anna %A Hotho, Andreas %B Proceedings of the 9th International Conference on Sensor Networks (SENSORNETS 2020) %D 2020 %I SCITEPRESS – Science and Technology Publications, Lda. %N 9 %P 142-149 %T Anomaly Detection in Beehives using Deep Recurrent Autoencoders
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  Evaluation of post-hoc XAI approaches through synthetic tabular data. Tritscher, Julian; Ring, Markus; Schlör, Daniel; Hettinger, Lena; Hotho, Andreas in International Symposium on Methodologies for Intelligent Systems (2020).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  Evaluating the explanations given by post-hoc XAI approaches on tabular data is a challenging prospect, since the subjective judgement of explanations of tabular relations is non trivial in contrast to e.g. the judgement of image heatmap explanations. In order to quantify XAI performance on categorical tabular data, where feature relationships can often be described by Boolean functions, we propose an evaluation setting through generation of synthetic datasets. To create gold standard explanations, we present a definition of feature relevance in Boolean functions. In the proposed setting we evaluate eight state-of-the-art XAI approaches and gain novel insights into XAI performance on categorical tabular data. We find that the investigated approaches often fail to faithfully explain even basic relationships within categorical data.
  @article{tritscher2020evaluation, abstract = {Evaluating the explanations given by post-hoc XAI approaches on tabular data is a challenging prospect, since the subjective judgement of explanations of tabular relations is non trivial in contrast to e.g. the judgement of image heatmap explanations. In order to quantify XAI performance on categorical tabular data, where feature relationships can often be described by Boolean functions, we propose an evaluation setting through generation of synthetic datasets. To create gold standard explanations, we present a definition of feature relevance in Boolean functions. In the proposed setting we evaluate eight state-of-the-art XAI approaches and gain novel insights into XAI performance on categorical tabular data. We find that the investigated approaches often fail to faithfully explain even basic relationships within categorical data.}, author = {Tritscher, Julian and Ring, Markus and Schlör, Daniel and Hettinger, Lena and Hotho, Andreas}, booktitle = {International Symposium on Methodologies for Intelligent Systems}, keywords = {dataset evaluation myown xai from:tritsch}, note = {Accepted but not published}, organization = {Springer}, title = {Evaluation of post-hoc XAI approaches through synthetic tabular data}, year = 2020 }
  %0 Journal Article %1 tritscher2020evaluation %A Tritscher, Julian %A Ring, Markus %A Schlör, Daniel %A Hettinger, Lena %A Hotho, Andreas %B International Symposium on Methodologies for Intelligent Systems %D 2020 %T Evaluation of post-hoc XAI approaches through synthetic tabular data %X Evaluating the explanations given by post-hoc XAI approaches on tabular data is a challenging prospect, since the subjective judgement of explanations of tabular relations is non trivial in contrast to e.g. the judgement of image heatmap explanations. In order to quantify XAI performance on categorical tabular data, where feature relationships can often be described by Boolean functions, we propose an evaluation setting through generation of synthetic datasets. To create gold standard explanations, we present a definition of feature relevance in Boolean functions. In the proposed setting we evaluate eight state-of-the-art XAI approaches and gain novel insights into XAI performance on categorical tabular data. We find that the investigated approaches often fail to faithfully explain even basic relationships within categorical data.
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  SimLoss: Class Similarities in Cross Entropy. Kobs, Konstantin; Steininger, Michael; Zehe, Albin; Lautenschlager, Florian; Hotho, Andreas (2020).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  One common loss function in neural network classification tasks is Categorical Cross Entropy (CCE), which punishes all misclassifications equally. However, classes often have an inherent structure. For instance, classifying an image of a rose as "violet" is better than as "truck". We introduce SimLoss, a drop-in replacement for CCE that incorporates class similarities along with two techniques to construct such matrices from task-specific knowledge. We test SimLoss on Age Estimation and Image Classification and find that it brings significant improvements over CCE on several metrics. SimLoss therefore allows for explicit modeling of background knowledge by simply exchanging the loss function, while keeping the neural network architecture the same. Code and additional resources can be found at https://github.com/konstantinkobs/SimLoss.
  @misc{kobs2020simloss, abstract = {One common loss function in neural network classification tasks is Categorical Cross Entropy (CCE), which punishes all misclassifications equally. However, classes often have an inherent structure. For instance, classifying an image of a rose as "violet" is better than as "truck". We introduce SimLoss, a drop-in replacement for CCE that incorporates class similarities along with two techniques to construct such matrices from task-specific knowledge. We test SimLoss on Age Estimation and Image Classification and find that it brings significant improvements over CCE on several metrics. SimLoss therefore allows for explicit modeling of background knowledge by simply exchanging the loss function, while keeping the neural network architecture the same. Code and additional resources can be found at https://github.com/konstantinkobs/SimLoss.}, author = {Kobs, Konstantin and Steininger, Michael and Zehe, Albin and Lautenschlager, Florian and Hotho, Andreas}, keywords = {crossentropy lossfunction myown from:konstantinkobs}, note = {cite arxiv:2003.03182Comment: This paper is going to be published in the proceedings of the 25th International Symposium on Methodologies for Intelligent Systems (ISMIS)}, title = {SimLoss: Class Similarities in Cross Entropy}, year = 2020 }
  %0 Generic %1 kobs2020simloss %A Kobs, Konstantin %A Steininger, Michael %A Zehe, Albin %A Lautenschlager, Florian %A Hotho, Andreas %D 2020 %T SimLoss: Class Similarities in Cross Entropy %U http://arxiv.org/abs/2003.03182 %X One common loss function in neural network classification tasks is Categorical Cross Entropy (CCE), which punishes all misclassifications equally. However, classes often have an inherent structure. For instance, classifying an image of a rose as "violet" is better than as "truck". We introduce SimLoss, a drop-in replacement for CCE that incorporates class similarities along with two techniques to construct such matrices from task-specific knowledge. We test SimLoss on Age Estimation and Image Classification and find that it brings significant improvements over CCE on several metrics. SimLoss therefore allows for explicit modeling of background knowledge by simply exchanging the loss function, while keeping the neural network architecture the same. Code and additional resources can be found at https://github.com/konstantinkobs/SimLoss.
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  Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels. Kobs, Konstantin; Zehe, Albin; Bernstetter, Armin; Chibane, Julian; Pfister, Jan; Tritscher, Julian; Hotho, Andreas in ACM Transactions on Social Computing (2020).
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  @article{noauthororeditor, author = {Kobs, Konstantin and Zehe, Albin and Bernstetter, Armin and Chibane, Julian and Pfister, Jan and Tritscher, Julian and Hotho, Andreas}, journal = {ACM Transactions on Social Computing}, keywords = {emote myown nlp semantic sentiment-analysis twitch from:konstantinkobs}, note = {accepted but not published}, title = {Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels}, year = 2020 }
  %0 Journal Article %1 noauthororeditor %A Kobs, Konstantin %A Zehe, Albin %A Bernstetter, Armin %A Chibane, Julian %A Pfister, Jan %A Tritscher, Julian %A Hotho, Andreas %D 2020 %J ACM Transactions on Social Computing %R 10.1145/3365523 %T Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels

2019 [ to top ]

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  EClaiRE: Context Matters! – Comparing Word Embeddings for Relation Classification. Hettinger, Lena; Zehe, Albin; Dallmann, Alexander; Hotho, Andreas K. David, Geihs, K., Lange, M., Stumme, G. (eds.) (2019). 191-204.
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  @inproceedings{mci/Hettinger2019, address = {Bonn}, author = {Hettinger, Lena and Zehe, Albin and Dallmann, Alexander and Hotho, Andreas}, booktitle = {INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft}, editor = {David, Klaus and Geihs, Kurt and Lange, Martin and Stumme, Gerd}, keywords = {classification embeddings myown relation semeval10 semeval18 word word_embedding from:schwemmlein}, pages = {191-204}, publisher = {Gesellschaft für Informatik e.V.}, title = {EClaiRE: Context Matters! – Comparing Word Embeddings for Relation Classification}, year = 2019 }
  %0 Conference Paper %1 mci/Hettinger2019 %A Hettinger, Lena %A Zehe, Albin %A Dallmann, Alexander %A Hotho, Andreas %B INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft %C Bonn %D 2019 %E David, Klaus %E Geihs, Kurt %E Lange, Martin %E Stumme, Gerd %I Gesellschaft für Informatik e.V. %P 191-204 %T EClaiRE: Context Matters! – Comparing Word Embeddings for Relation Classification
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  Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks. Zehe, Albin; Hettinger, Lena; Ernst, Stefan; Hauptmann, Christian; Hotho, Andreas (2019).
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  @inproceedings{zehe2019xenophilius, author = {Zehe, Albin and Hettinger, Lena and Ernst, Stefan and Hauptmann, Christian and Hotho, Andreas}, booktitle = {Proceedings of The 13th International Workshop on Semantic Evaluation}, keywords = {cnn hyperpartisan myown neuralnets semeval from:albinzehe}, publisher = {Association for Computational Linguistics}, title = {Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks}, year = 2019 }
  %0 Conference Paper %1 zehe2019xenophilius %A Zehe, Albin %A Hettinger, Lena %A Ernst, Stefan %A Hauptmann, Christian %A Hotho, Andreas %B Proceedings of The 13th International Workshop on Semantic Evaluation %D 2019 %I Association for Computational Linguistics %T Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks
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  Flow-based network traffic generation using Generative Adversarial Networks. Ring, Markus; Schlör, Daniel; Landes, Dieter; Hotho, Andreas in Computers & Security (2019). 82 156 - 172.
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  Flow-based data sets are necessary for evaluating network-based intrusion detection systems (NIDS). In this work, we propose a novel methodology for generating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation. A major challenge lies in the fact that GANs can only process continuous attributes. However, flow-based data inevitably contain categorical attributes such as IP addresses or port numbers. Therefore, we propose three different preprocessing approaches for flow-based data in order to transform them into continuous values. Further, we present a new method for evaluating the generated flow-based network traffic which uses domain knowledge to define quality tests. We use the three approaches for generating flow-based network traffic based on the CIDDS-001 data set. Experiments indicate that two of the three approaches are able to generate high quality data.
  @article{RING2019156, abstract = {Flow-based data sets are necessary for evaluating network-based intrusion detection systems (NIDS). In this work, we propose a novel methodology for generating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation. A major challenge lies in the fact that GANs can only process continuous attributes. However, flow-based data inevitably contain categorical attributes such as IP addresses or port numbers. Therefore, we propose three different preprocessing approaches for flow-based data in order to transform them into continuous values. Further, we present a new method for evaluating the generated flow-based network traffic which uses domain knowledge to define quality tests. We use the three approaches for generating flow-based network traffic based on the CIDDS-001 data set. Experiments indicate that two of the three approaches are able to generate high quality data.}, author = {Ring, Markus and Schlör, Daniel and Landes, Dieter and Hotho, Andreas}, journal = {Computers & Security}, keywords = {2019 GAN flow from:hotho generation myown network security security:selected traffic}, pages = {156 - 172}, title = {Flow-based network traffic generation using Generative Adversarial Networks}, volume = 82, year = 2019 }
  %0 Journal Article %1 RING2019156 %A Ring, Markus %A Schlör, Daniel %A Landes, Dieter %A Hotho, Andreas %D 2019 %J Computers & Security %P 156 - 172 %R https://doi.org/10.1016/j.cose.2018.12.012 %T Flow-based network traffic generation using Generative Adversarial Networks %U http://www.sciencedirect.com/science/article/pii/S0167404818308393 %V 82 %X Flow-based data sets are necessary for evaluating network-based intrusion detection systems (NIDS). In this work, we propose a novel methodology for generating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation. A major challenge lies in the fact that GANs can only process continuous attributes. However, flow-based data inevitably contain categorical attributes such as IP addresses or port numbers. Therefore, we propose three different preprocessing approaches for flow-based data in order to transform them into continuous values. Further, we present a new method for evaluating the generated flow-based network traffic which uses domain knowledge to define quality tests. We use the three approaches for generating flow-based network traffic based on the CIDDS-001 data set. Experiments indicate that two of the three approaches are able to generate high quality data.
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  Detection of Scenes in Fiction. Gius, Evelyn; Jannidis, Fotis; Krug, Markus; Zehe, Albin; Hotho, Andreas; Puppe, Frank; Krebs, Jonathan; Reiter, Nils; Wiedmer, Nathalie; Konle, Leonard (2019).
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  @inproceedings{gius2019detection, author = {Gius, Evelyn and Jannidis, Fotis and Krug, Markus and Zehe, Albin and Hotho, Andreas and Puppe, Frank and Krebs, Jonathan and Reiter, Nils and Wiedmer, Nathalie and Konle, Leonard}, booktitle = {Proceedings of Digital Humanities 2019}, keywords = {dh dh2019 kallimachos myown nlp scenedetection scenes from:albinzehe}, title = {Detection of Scenes in Fiction}, year = 2019 }
  %0 Conference Paper %1 gius2019detection %A Gius, Evelyn %A Jannidis, Fotis %A Krug, Markus %A Zehe, Albin %A Hotho, Andreas %A Puppe, Frank %A Krebs, Jonathan %A Reiter, Nils %A Wiedmer, Nathalie %A Konle, Leonard %B Proceedings of Digital Humanities 2019 %D 2019 %T Detection of Scenes in Fiction
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  On the Right Track! Analysing and Predicting Navigation Success in Wikipedia. Koopmann, Tobias; Dallmann, Alexander; Hettinger, Lena; Niebler, Thomas; Hotho, Andreas in HT '19 (2019). 143--152.
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  @inproceedings{Koopmann:2019:RTA:3342220.3343650, address = {New York, NY, USA}, author = {Koopmann, Tobias and Dallmann, Alexander and Hettinger, Lena and Niebler, Thomas and Hotho, Andreas}, booktitle = {Proceedings of the 30th ACM Conference on Hypertext and Social Media}, keywords = {behaviour modelling myown navigation path prediction success user web wikipedia from:schwemmlein}, pages = {143–152}, publisher = {ACM}, series = {HT '19}, title = {On the Right Track! Analysing and Predicting Navigation Success in Wikipedia}, year = 2019 }
  %0 Conference Paper %1 Koopmann:2019:RTA:3342220.3343650 %A Koopmann, Tobias %A Dallmann, Alexander %A Hettinger, Lena %A Niebler, Thomas %A Hotho, Andreas %B Proceedings of the 30th ACM Conference on Hypertext and Social Media %C New York, NY, USA %D 2019 %I ACM %P 143--152 %R 10.1145/3342220.3343650 %T On the Right Track! Analysing and Predicting Navigation Success in Wikipedia %U http://doi.acm.org/10.1145/3342220.3343650 %@ 978-1-4503-6885-8
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  Solving Mathematical Exercises: Prediction of Students’ Success. Wankerl, Sebastian; Götz, Gerhard; Hotho, Andreas in CEUR Workshop Proceedings, R. Jäschke, Weidlich, M. (eds.) (2019). (Vol. 2454) 190-194.
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  @inproceedings{wankerl2019solving, author = {Wankerl, Sebastian and Götz, Gerhard and Hotho, Andreas}, booktitle = {LWDA}, editor = {Jäschke, Robert and Weidlich, Matthias}, keywords = {2019 imported myown from:hotho}, pages = {190-194}, publisher = {CEUR-WS.org}, series = {CEUR Workshop Proceedings}, title = {Solving Mathematical Exercises: Prediction of Students’ Success}, volume = 2454, year = 2019 }
  %0 Conference Paper %1 wankerl2019solving %A Wankerl, Sebastian %A Götz, Gerhard %A Hotho, Andreas %B LWDA %D 2019 %E Jäschke, Robert %E Weidlich, Matthias %I CEUR-WS.org %P 190-194 %T Solving Mathematical Exercises: Prediction of Students’ Success %U http://ceur-ws.org/Vol-2454/paper_84.pdf %V 2454
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  Comparison of System Call Representations for Intrusion Detection. Wunderlich, Sarah; Ring, Markus; Landes, Dieter; Hotho, Andreas (2019).
  [ BibTeX ] [ EndNote ]
   
  @article{wunderlich2019comparison, author = {Wunderlich, Sarah and Ring, Markus and Landes, Dieter and Hotho, Andreas}, keywords = {call comparison detection from:nosebrain intrusion myown representation system}, title = {Comparison of System Call Representations for Intrusion Detection}, year = 2019 }
  %0 Journal Article %1 wunderlich2019comparison %A Wunderlich, Sarah %A Ring, Markus %A Landes, Dieter %A Hotho, Andreas %D 2019 %T Comparison of System Call Representations for Intrusion Detection
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  A survey of network-based intrusion detection data sets. Ring, Markus; Wunderlich, Sarah; Scheuring, Deniz; Landes, Dieter; Hotho, Andreas in Comput. Secur. (2019). 86 147-167.
  [ BibTeX ] [ EndNote ] [ URL ]
   
  @article{ring2019survey, author = {Ring, Markus and Wunderlich, Sarah and Scheuring, Deniz and Landes, Dieter and Hotho, Andreas}, journal = {Comput. Secur.}, keywords = {datasets detection intrusion myown network-based survey}, pages = {147-167}, title = {A survey of network-based intrusion detection data sets}, volume = 86, year = 2019 }
  %0 Journal Article %1 ring2019survey %A Ring, Markus %A Wunderlich, Sarah %A Scheuring, Deniz %A Landes, Dieter %A Hotho, Andreas %D 2019 %J Comput. Secur. %P 147-167 %T A survey of network-based intrusion detection data sets %U http://dblp.uni-trier.de/db/journals/compsec/compsec86.html#RingWSLH19 %V 86

2018 [ to top ]

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  Big-Data Helps SDN to Improve Application Specific Quality of Service. Schwarzmann, Susanna; Blenk, Andreas; Dobrijevic, Ognjen; Jarschel, Michael; Hotho, Andreas; Zinner, Thomas; Wamser, Florian in Big Data and Software Defined Networks (2018).
  [ Abstract ] [ BibTeX ] [ EndNote ]
   
  This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.
  @incollection{schwarzmann2018bigdata, abstract = {This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.}, author = {Schwarzmann, Susanna and Blenk, Andreas and Dobrijevic, Ognjen and Jarschel, Michael and Hotho, Andreas and Zinner, Thomas and Wamser, Florian}, booktitle = {Big Data and Software Defined Networks}, keywords = {big data from:hotho myown network quality sdn service}, publisher = {IET}, title = {Big-Data Helps SDN to Improve Application Specific Quality of Service}, year = 2018 }
  %0 Book Section %1 schwarzmann2018bigdata %A Schwarzmann, Susanna %A Blenk, Andreas %A Dobrijevic, Ognjen %A Jarschel, Michael %A Hotho, Andreas %A Zinner, Thomas %A Wamser, Florian %B Big Data and Software Defined Networks %D 2018 %I IET %T Big-Data Helps SDN to Improve Application Specific Quality of Service %X This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.
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  Burrows Zeta: Varianten und Evaluation. Schöch, Christof; Calvo, José; Zehe, Albin; Hotho, Andreas (2018).
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  @inproceedings{schoch2018burrows, author = {Schöch, Christof and Calvo, José and Zehe, Albin and Hotho, Andreas}, booktitle = {DHd 2018}, keywords = {cligs dh from:albinzehe myown zeta}, title = {Burrows Zeta: Varianten und Evaluation}, year = 2018 }
  %0 Conference Paper %1 schoch2018burrows %A Schöch, Christof %A Calvo, José %A Zehe, Albin %A Hotho, Andreas %B DHd 2018 %D 2018 %T Burrows Zeta: Varianten und Evaluation
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  Analysing Direct Speech in German Novels. Jannidis, Fotis; Konle, Leonard; Zehe, Albin; Hotho, Andreas; Krug, Markus (2018).
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  @inproceedings{jannidis2018analysing, author = {Jannidis, Fotis and Konle, Leonard and Zehe, Albin and Hotho, Andreas and Krug, Markus}, booktitle = {DHd 2018}, keywords = {dh directspeech from:albinzehe kallimachos myown}, title = {Analysing Direct Speech in German Novels}, year = 2018 }
  %0 Conference Paper %1 jannidis2018analysing %A Jannidis, Fotis %A Konle, Leonard %A Zehe, Albin %A Hotho, Andreas %A Krug, Markus %B DHd 2018 %D 2018 %T Analysing Direct Speech in German Novels
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  ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings. Hettinger, Lena; Dallmann, Alexander; Zehe, Albin; Niebler, Thomas; Hotho, Andreas (2018).
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  @inproceedings{hettinger2018semeval, address = {New Orleans, LA, USA}, author = {Hettinger, Lena and Dallmann, Alexander and Zehe, Albin and Niebler, Thomas and Hotho, Andreas}, booktitle = {Proceedings of International Workshop on Semantic Evaluation (SemEval-2018)}, keywords = {2018 classification embeddings from:schwemmlein myown relation scientific semantic semantic:selected semeval w2v word}, title = {ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings}, year = 2018 }
  %0 Conference Paper %1 hettinger2018semeval %A Hettinger, Lena %A Dallmann, Alexander %A Zehe, Albin %A Niebler, Thomas %A Hotho, Andreas %B Proceedings of International Workshop on Semantic Evaluation (SemEval-2018) %C New Orleans, LA, USA %D 2018 %T ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings
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  ClaiRE at SemEval-2018 Task 7 - Extended Version. Hettinger, Lena; Dallmann, Alexander; Zehe, Albin; Niebler, Thomas; Hotho, Andreas (2018).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  In this paper we describe our post-evaluation results for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1.1) and noisy data (subtask 1.2). Due to space limitations we publish an extended version of Hettinger et al. (2018) including further technical details and changes made to the preprocessing step in the post-evaluation phase. Due to these changes Classification of Relations using Embeddings (ClaiRE) achieved an improved F1 score of 75.11% for the first subtask and 81.44% for the second.
  @misc{hettinger2018claire, abstract = {In this paper we describe our post-evaluation results for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1.1) and noisy data (subtask 1.2). Due to space limitations we publish an extended version of Hettinger et al. (2018) including further technical details and changes made to the preprocessing step in the post-evaluation phase. Due to these changes Classification of Relations using Embeddings (ClaiRE) achieved an improved F1 score of 75.11% for the first subtask and 81.44% for the second.}, author = {Hettinger, Lena and Dallmann, Alexander and Zehe, Albin and Niebler, Thomas and Hotho, Andreas}, keywords = {extraction from:thoni myown relation scientific semantic semeval tagging}, note = {cite arxiv:1804.05825Comment: This is the extended version for our work: ClaiRE at SemEval-2018 Task 7}, title = {ClaiRE at SemEval-2018 Task 7 - Extended Version}, year = 2018 }
  %0 Generic %1 hettinger2018claire %A Hettinger, Lena %A Dallmann, Alexander %A Zehe, Albin %A Niebler, Thomas %A Hotho, Andreas %D 2018 %T ClaiRE at SemEval-2018 Task 7 - Extended Version %U http://arxiv.org/abs/1804.05825 %X In this paper we describe our post-evaluation results for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1.1) and noisy data (subtask 1.2). Due to space limitations we publish an extended version of Hettinger et al. (2018) including further technical details and changes made to the preprocessing step in the post-evaluation phase. Due to these changes Classification of Relations using Embeddings (ClaiRE) achieved an improved F1 score of 75.11% for the first subtask and 81.44% for the second.
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  A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels. Zehe, Albin; Schlör, Daniel; Henny-Krahmer, Ulrike; Becker, Martin; Hotho, Andreas (2018).
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  @inproceedings{zehe2018whitebox, author = {Zehe, Albin and Schlör, Daniel and Henny-Krahmer, Ulrike and Becker, Martin and Hotho, Andreas}, booktitle = {DH}, keywords = {author classification cligs dh from:albinzehe myown nationality svn}, organization = {ADHO}, title = {A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels}, year = 2018 }
  %0 Conference Paper %1 zehe2018whitebox %A Zehe, Albin %A Schlör, Daniel %A Henny-Krahmer, Ulrike %A Becker, Martin %A Hotho, Andreas %B DH %D 2018 %T A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels
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  Healing Time Correlates With the Quality of Scaring: Results From a Prospective Randomized Control Donor Site Trial. Werdin, Frank; Tenenhaus, Mayer; Becker, Martin; Rennekampff, Hans-Oliver in Dermatologic Surgery (2018). 44(4) 521--527.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @article{werdin2018healing, author = {Werdin, Frank and Tenenhaus, Mayer and Becker, Martin and Rennekampff, Hans-Oliver}, journal = {Dermatologic Surgery}, keywords = {healing medicin myown scar statistical test time tissue from:becker}, number = 4, pages = {521–527}, publisher = {LWW}, title = {Healing Time Correlates With the Quality of Scaring: Results From a Prospective Randomized Control Donor Site Trial}, volume = 44, year = 2018 }
  %0 Journal Article %1 werdin2018healing %A Werdin, Frank %A Tenenhaus, Mayer %A Becker, Martin %A Rennekampff, Hans-Oliver %D 2018 %I LWW %J Dermatologic Surgery %N 4 %P 521--527 %T Healing Time Correlates With the Quality of Scaring: Results From a Prospective Randomized Control Donor Site Trial %V 44
• 
  Accessing Information with Tags: Search and Ranking. Navarro Bullock, Beate; Hotho, Andreas; Stumme, Gerd in Social Information Access: Systems and Technologies, P. Brusilovsky, He, D. (eds.) (2018). 310--343.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  With the growth of the Social Web, a variety of new web-based services arose and changed the way users interact with the internet and consume information. One central phenomenon was and is tagging which allows to manage, organize and access information in social systems. Tagging helps to manage all kinds of resources, making their access much easier. The first type of social tagging systems were social bookmarking systems, i.e., platforms for storing and sharing bookmarks on the web rather than just in the browser. Meanwhile, (hash-)tagging is central in many other Social Media systems such as social networking sites and micro-blogging platforms. To allow for efficient information access, special algorithms have been developed to guide the user, to search for information and to rank the content based on tagging information contributed by the users.
  @inbook{navarrobullock2018accessing, abstract = {With the growth of the Social Web, a variety of new web-based services arose and changed the way users interact with the internet and consume information. One central phenomenon was and is tagging which allows to manage, organize and access information in social systems. Tagging helps to manage all kinds of resources, making their access much easier. The first type of social tagging systems were social bookmarking systems, i.e., platforms for storing and sharing bookmarks on the web rather than just in the browser. Meanwhile, (hash-)tagging is central in many other Social Media systems such as social networking sites and micro-blogging platforms. To allow for efficient information access, special algorithms have been developed to guide the user, to search for information and to rank the content based on tagging information contributed by the users.}, address = {Cham}, author = {Navarro Bullock, Beate and Hotho, Andreas and Stumme, Gerd}, booktitle = {Social Information Access: Systems and Technologies}, editor = {Brusilovsky, Peter and He, Daqing}, keywords = {folkrank folksonomy from:hotho myown rank search tag}, pages = {310–343}, publisher = {Springer International Publishing}, title = {Accessing Information with Tags: Search and Ranking}, year = 2018 }
  %0 Book Section %1 navarrobullock2018accessing %A Navarro Bullock, Beate %A Hotho, Andreas %A Stumme, Gerd %B Social Information Access: Systems and Technologies %C Cham %D 2018 %E Brusilovsky, Peter %E He, Daqing %I Springer International Publishing %P 310--343 %R 10.1007/978-3-319-90092-6_9 %T Accessing Information with Tags: Search and Ranking %U https://doi.org/10.1007/978-3-319-90092-6_9 %X With the growth of the Social Web, a variety of new web-based services arose and changed the way users interact with the internet and consume information. One central phenomenon was and is tagging which allows to manage, organize and access information in social systems. Tagging helps to manage all kinds of resources, making their access much easier. The first type of social tagging systems were social bookmarking systems, i.e., platforms for storing and sharing bookmarks on the web rather than just in the browser. Meanwhile, (hash-)tagging is central in many other Social Media systems such as social networking sites and micro-blogging platforms. To allow for efficient information access, special algorithms have been developed to guide the user, to search for information and to rank the content based on tagging information contributed by the users. %@ 978-3-319-90092-6
• 
  Burrows’ Zeta: Exploring and Evaluating Variants and Parameters. Schöch, Christof; Schlör, Daniel; Zehe, Albin; Gebhard, Henning; Becker, Martin; Hotho, Andreas (2018). 274-277.
  [ BibTeX ] [ EndNote ] [ URL ]
   
  @inproceedings{schoech2018zeta, author = {Schöch, Christof and Schlör, Daniel and Zehe, Albin and Gebhard, Henning and Becker, Martin and Hotho, Andreas}, booktitle = {DH}, keywords = {cligs dh from:albinzehe myown zeta}, pages = {274-277}, title = {Burrows’ Zeta: Exploring and Evaluating Variants and Parameters}, year = 2018 }
  %0 Conference Paper %1 schoech2018zeta %A Schöch, Christof %A Schlör, Daniel %A Zehe, Albin %A Gebhard, Henning %A Becker, Martin %A Hotho, Andreas %B DH %D 2018 %P 274-277 %T Burrows’ Zeta: Exploring and Evaluating Variants and Parameters %U http://dblp.uni-trier.de/db/conf/dihu/dh2018.html#SchochSZG0H18
• 
  EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data. Lautenschlager, Florian; Becker, Martin; Steininger, Michael; Hotho, Andreas D. Burghardt, Chen, S., Andrienko, G., Andrienko, N., Purves, R., Diehl, A. (eds.) (2018).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{lautenschlager2018everyaware, author = {Lautenschlager, Florian and Becker, Martin and Steininger, Michael and Hotho, Andreas}, booktitle = {Proceedings of VGI Geovisual Analytics Workshop, colocated with BDVA 2018}, editor = {Burghardt, Dirk and Chen, Siming and Andrienko, Gennady and Andrienko, Nathalia and Purves, Ross and Diehl, Alexandra}, keywords = {everyaware from:lautenschlager myown p2map2:antrag:own project:p2map}, month = {oct}, publisher = {KOPS}, title = {EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data}, year = 2018 }
  %0 Conference Paper %1 lautenschlager2018everyaware %A Lautenschlager, Florian %A Becker, Martin %A Steininger, Michael %A Hotho, Andreas %B Proceedings of VGI Geovisual Analytics Workshop, colocated with BDVA 2018 %D 2018 %E Burghardt, Dirk %E Chen, Siming %E Andrienko, Gennady %E Andrienko, Nathalia %E Purves, Ross %E Diehl, Alexandra %I KOPS %T EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data
• 
  Air Trails -- Urban Air Quality Campaign Exploration Patterns. Becker, Martin; Lautenschlager, Florian; Hotho, Andreas (2018).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @article{becker2018air, author = {Becker, Martin and Lautenschlager, Florian and Hotho, Andreas}, keywords = {airtrails exploration human hyptrails mobility myown pattern project:p2map}, title = {Air Trails – Urban Air Quality Campaign Exploration Patterns}, year = 2018 }
  %0 Journal Article %1 becker2018air %A Becker, Martin %A Lautenschlager, Florian %A Hotho, Andreas %D 2018 %T Air Trails -- Urban Air Quality Campaign Exploration Patterns
• 
  pysubgroup: Easy-to-Use Subgroup Discovery in Python. Lemmerich, Florian; Becker, Martin in Lecture Notes in Computer Science, U. Brefeld, Curry, E., Daly, E., MacNamee, B., Marascu, A., Pinelli, F., Berlingerio, M., Hurley, N. (eds.) (2018). (Vol. 11053) 658-662.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{lemmerich2018pysubgroup, author = {Lemmerich, Florian and Becker, Martin}, booktitle = {ECML/PKDD (3)}, crossref = {conf/pkdd/2018-3}, editor = {Brefeld, Ulf and Curry, Edward and Daly, Elizabeth and MacNamee, Brian and Marascu, Alice and Pinelli, Fabio and Berlingerio, Michele and Hurley, Neil}, keywords = {myown from:becker}, pages = {658-662}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {pysubgroup: Easy-to-Use Subgroup Discovery in Python.}, volume = 11053, year = 2018 }
  %0 Conference Paper %1 lemmerich2018pysubgroup %A Lemmerich, Florian %A Becker, Martin %B ECML/PKDD (3) %D 2018 %E Brefeld, Ulf %E Curry, Edward %E Daly, Elizabeth %E MacNamee, Brian %E Marascu, Alice %E Pinelli, Fabio %E Berlingerio, Michele %E Hurley, Neil %I Springer %P 658-662 %T pysubgroup: Easy-to-Use Subgroup Discovery in Python. %U http://dblp.uni-trier.de/db/conf/pkdd/pkdd2018-3.html#Lemmerich018 %V 11053 %@ 978-3-030-10997-4
• 
  Flow-based Network Traffic Generation using Generative Adversarial Networks. Ring, Markus; Schlör, Daniel; Landes, Dieter; Hotho, Andreas in CoRR (2018). abs/1810.07795
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  Flow-based data sets are necessary for evaluating network-based intrusion de- tection systems (NIDS). In this work, we propose a novel methodology for gener- ating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation. A major challenge lies in the fact that GANs can only process continuous at- tributes. However, flow-based data inevitably contain categorical attributes such as IP addresses or port numbers. Therefore, we propose three different preprocessing approaches for flow-based data in order to transform them into continuous values. Further, we present a new method for evaluating the gener- ated flow-based network traffic which uses domain knowledge to define quality tests. We use the three approaches for generating flow-based network traffic based on the CIDDS-001 data set. Experiments indicate that two of the three approaches are able to generate high quality data.
  @article{ring2018flowbased, abstract = {Flow-based data sets are necessary for evaluating network-based intrusion de- tection systems (NIDS). In this work, we propose a novel methodology for gener- ating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation. A major challenge lies in the fact that GANs can only process continuous at- tributes. However, flow-based data inevitably contain categorical attributes such as IP addresses or port numbers. Therefore, we propose three different preprocessing approaches for flow-based data in order to transform them into continuous values. Further, we present a new method for evaluating the gener- ated flow-based network traffic which uses domain knowledge to define quality tests. We use the three approaches for generating flow-based network traffic based on the CIDDS-001 data set. Experiments indicate that two of the three approaches are able to generate high quality data.}, author = {Ring, Markus and Schlör, Daniel and Landes, Dieter and Hotho, Andreas}, journal = {CoRR}, keywords = {myown}, title = {Flow-based Network Traffic Generation using Generative Adversarial Networks.}, volume = {abs/1810.07795}, year = 2018 }
  %0 Journal Article %1 ring2018flowbased %A Ring, Markus %A Schlör, Daniel %A Landes, Dieter %A Hotho, Andreas %D 2018 %J CoRR %T Flow-based Network Traffic Generation using Generative Adversarial Networks. %U http://dblp.uni-trier.de/db/journals/corr/corr1810.html#abs-1810-07795 %V abs/1810.07795 %X Flow-based data sets are necessary for evaluating network-based intrusion de- tection systems (NIDS). In this work, we propose a novel methodology for gener- ating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation. A major challenge lies in the fact that GANs can only process continuous at- tributes. However, flow-based data inevitably contain categorical attributes such as IP addresses or port numbers. Therefore, we propose three different preprocessing approaches for flow-based data in order to transform them into continuous values. Further, we present a new method for evaluating the gener- ated flow-based network traffic which uses domain knowledge to define quality tests. We use the three approaches for generating flow-based network traffic based on the CIDDS-001 data set. Experiments indicate that two of the three approaches are able to generate high quality data.
• 
  Detection of slow port scans in flow-based network traffic. Ring, Markus; Landes, Dieter; Hotho, Andreas in PLOS ONE (2018). 13(9) 1-18.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  Frequently, port scans are early indicators of more serious attacks. Unfortunately, the detection of slow port scans in company networks is challenging due to the massive amount of network data. This paper proposes an innovative approach for preprocessing flow-based data which is specifically tailored to the detection of slow port scans. The preprocessing chain generates new objects based on flow-based data aggregated over time windows while taking domain knowledge as well as additional knowledge about the network structure into account. The computed objects are used as input for the further analysis. Based on these objects, we propose two different approaches for detection of slow port scans. One approach is unsupervised and uses sequential hypothesis testing whereas the other approach is supervised and uses classification algorithms. We compare both approaches with existing port scan detection algorithms on the flow-based CIDDS-001 data set. Experiments indicate that the proposed approaches achieve better detection rates and exhibit less false alarms than similar algorithms.
  @article{10.1371/journal.pone.0204507, abstract = {Frequently, port scans are early indicators of more serious attacks. Unfortunately, the detection of slow port scans in company networks is challenging due to the massive amount of network data. This paper proposes an innovative approach for preprocessing flow-based data which is specifically tailored to the detection of slow port scans. The preprocessing chain generates new objects based on flow-based data aggregated over time windows while taking domain knowledge as well as additional knowledge about the network structure into account. The computed objects are used as input for the further analysis. Based on these objects, we propose two different approaches for detection of slow port scans. One approach is unsupervised and uses sequential hypothesis testing whereas the other approach is supervised and uses classification algorithms. We compare both approaches with existing port scan detection algorithms on the flow-based CIDDS-001 data set. Experiments indicate that the proposed approaches achieve better detection rates and exhibit less false alarms than similar algorithms.}, author = {Ring, Markus and Landes, Dieter and Hotho, Andreas}, journal = {PLOS ONE}, keywords = {myown}, month = {09}, number = 9, pages = {1-18}, publisher = {Public Library of Science}, title = {Detection of slow port scans in flow-based network traffic}, volume = 13, year = 2018 }
  %0 Journal Article %1 10.1371/journal.pone.0204507 %A Ring, Markus %A Landes, Dieter %A Hotho, Andreas %D 2018 %I Public Library of Science %J PLOS ONE %N 9 %P 1-18 %R 10.1371/journal.pone.0204507 %T Detection of slow port scans in flow-based network traffic %U https://doi.org/10.1371/journal.pone.0204507 %V 13 %X Frequently, port scans are early indicators of more serious attacks. Unfortunately, the detection of slow port scans in company networks is challenging due to the massive amount of network data. This paper proposes an innovative approach for preprocessing flow-based data which is specifically tailored to the detection of slow port scans. The preprocessing chain generates new objects based on flow-based data aggregated over time windows while taking domain knowledge as well as additional knowledge about the network structure into account. The computed objects are used as input for the further analysis. Based on these objects, we propose two different approaches for detection of slow port scans. One approach is unsupervised and uses sequential hypothesis testing whereas the other approach is supervised and uses classification algorithms. We compare both approaches with existing port scan detection algorithms on the flow-based CIDDS-001 data set. Experiments indicate that the proposed approaches achieve better detection rates and exhibit less false alarms than similar algorithms.
• 
  Adaptive kNN Using Expected Accuracy for Classification of Geo-spatial Data. Kibanov, Mark; Becker, Martin; Müller, Juergen; Atzmüller, Martin; Hotho, Andreas; Stumme, Gerd in SAC '18 (2018). 857--865.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  The k-Nearest Neighbor (kNN) classification approach is conceptually simple - yet widely applied since it often performs well in practical applications. However, using a global constant k does not always provide an optimal solution, e. g., for datasets with an irregular density distribution of data points. This paper proposes an adaptive kNN classifier where k is chosen dynamically for each instance (point) to be classified, such that the expected accuracy of classification is maximized. We define the expected accuracy as the accuracy of a set of structurally similar observations. An arbitrary similarity function can be used to find these observations. We introduce and evaluate different similarity functions. For the evaluation, we use five different classification tasks based on geo-spatial data. Each classification task consists of (tens of) thousands of items. We demonstrate, that the presented expected accuracy measures can be a good estimator for kNN performance, and the proposed adaptive kNN classifier outperforms common kNN and previously introduced adaptive kNN algorithms. Also, we show that the range of considered k can be significantly reduced to speed up the algorithm without negative influence on classification accuracy.
  @inproceedings{kibanov2018adaptive, abstract = {The k-Nearest Neighbor (kNN) classification approach is conceptually simple - yet widely applied since it often performs well in practical applications. However, using a global constant k does not always provide an optimal solution, e. g., for datasets with an irregular density distribution of data points. This paper proposes an adaptive kNN classifier where k is chosen dynamically for each instance (point) to be classified, such that the expected accuracy of classification is maximized. We define the expected accuracy as the accuracy of a set of structurally similar observations. An arbitrary similarity function can be used to find these observations. We introduce and evaluate different similarity functions. For the evaluation, we use five different classification tasks based on geo-spatial data. Each classification task consists of (tens of) thousands of items. We demonstrate, that the presented expected accuracy measures can be a good estimator for kNN performance, and the proposed adaptive kNN classifier outperforms common kNN and previously introduced adaptive kNN algorithms. Also, we show that the range of considered k can be significantly reduced to speed up the algorithm without negative influence on classification accuracy.}, address = {New York, NY, USA}, author = {Kibanov, Mark and Becker, Martin and Müller, Juergen and Atzmüller, Martin and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proceedings of the 33rd Annual ACM Symposium on Applied Computing}, keywords = {accuracy adaptive eva everyaware expected from:becker geo kassel knn myown spatial}, pages = {857–865}, publisher = {ACM}, series = {SAC '18}, title = {Adaptive kNN Using Expected Accuracy for Classification of Geo-spatial Data}, year = 2018 }
  %0 Conference Paper %1 kibanov2018adaptive %A Kibanov, Mark %A Becker, Martin %A Müller, Juergen %A Atzmüller, Martin %A Hotho, Andreas %A Stumme, Gerd %B Proceedings of the 33rd Annual ACM Symposium on Applied Computing %C New York, NY, USA %D 2018 %I ACM %P 857--865 %R 10.1145/3167132.3167226 %T Adaptive kNN Using Expected Accuracy for Classification of Geo-spatial Data %U http://doi.acm.org/10.1145/3167132.3167226 %X The k-Nearest Neighbor (kNN) classification approach is conceptually simple - yet widely applied since it often performs well in practical applications. However, using a global constant k does not always provide an optimal solution, e. g., for datasets with an irregular density distribution of data points. This paper proposes an adaptive kNN classifier where k is chosen dynamically for each instance (point) to be classified, such that the expected accuracy of classification is maximized. We define the expected accuracy as the accuracy of a set of structurally similar observations. An arbitrary similarity function can be used to find these observations. We introduce and evaluate different similarity functions. For the evaluation, we use five different classification tasks based on geo-spatial data. Each classification task consists of (tens of) thousands of items. We demonstrate, that the presented expected accuracy measures can be a good estimator for kNN performance, and the proposed adaptive kNN classifier outperforms common kNN and previously introduced adaptive kNN algorithms. Also, we show that the range of considered k can be significantly reduced to speed up the algorithm without negative influence on classification accuracy. %@ 978-1-4503-5191-1

2017 [ to top ]

• 
  Leveraging User-Interactions for Time-Aware Tag Recommendations. Zoller, Daniel; Doerfel, Stephan; Pölitz, Christian; Hotho, Andreas in CEUR Workshop Proceedings (2017).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  For the popular task of tag recommendation, various (complex) approaches have been proposed. Recently however, research has focused on heuristics with low computational effort and particularly, a time-aware heuristic, called BLL, has been shown to compare well to various state-of-the-art methods. Here, we follow up on these results by presenting another time-aware approach leveraging user interaction data in an easily interpretable, on-the-fly computable approach that can successfully be combined with BLL. We investigate the influence of time as a parameter in that approach, and we demonstrate the effectiveness of the proposed method using two datasets from the popular public social tagging system BibSonomy.
  @inproceedings{zoller2017leveraging, abstract = {For the popular task of tag recommendation, various (complex) approaches have been proposed. Recently however, research has focused on heuristics with low computational effort and particularly, a time-aware heuristic, called BLL, has been shown to compare well to various state-of-the-art methods. Here, we follow up on these results by presenting another time-aware approach leveraging user interaction data in an easily interpretable, on-the-fly computable approach that can successfully be combined with BLL. We investigate the influence of time as a parameter in that approach, and we demonstrate the effectiveness of the proposed method using two datasets from the popular public social tagging system BibSonomy.}, author = {Zoller, Daniel and Doerfel, Stephan and Pölitz, Christian and Hotho, Andreas}, booktitle = {Proceedings of the Workshop on Temporal Reasoning in Recommender Systems}, keywords = {bibsonomy:selected from:nosebrain interaction myown project:bibsonomy recommendation recommender research:recommender research:recommender:selected tag user}, series = {{CEUR} Workshop Proceedings}, title = {Leveraging User-Interactions for Time-Aware Tag Recommendations}, year = 2017 }
  %0 Conference Paper %1 zoller2017leveraging %A Zoller, Daniel %A Doerfel, Stephan %A Pölitz, Christian %A Hotho, Andreas %B Proceedings of the Workshop on Temporal Reasoning in Recommender Systems %D 2017 %T Leveraging User-Interactions for Time-Aware Tag Recommendations %X For the popular task of tag recommendation, various (complex) approaches have been proposed. Recently however, research has focused on heuristics with low computational effort and particularly, a time-aware heuristic, called BLL, has been shown to compare well to various state-of-the-art methods. Here, we follow up on these results by presenting another time-aware approach leveraging user interaction data in an easily interpretable, on-the-fly computable approach that can successfully be combined with BLL. We investigate the influence of time as a parameter in that approach, and we demonstrate the effectiveness of the proposed method using two datasets from the popular public social tagging system BibSonomy.
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  Eleven-Week Preparation Involving Polarized Intensity Distribution Is Not Superior to Pyramidal Distribution in National Elite Rowers. Treff, Gunnar; Winkert, Kay; Sareban, Mahdi; Steinacker, Jürgen M.; Becker, Martin; Sperlich, Billy in Frontiers in Physiology (2017). 8 515.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Polarized (POL) training intensity distribution (TID) emphasizes high-volume low-intensity exercise in zone (Z)1 (< first lactate threshold) with a greater proportion of high-intensity Z3 (> second lactate threshold) compared to Z2 (between first and second lactate threshold). In highly trained rowers there is a lack of prospective controlled evidence whether POL is superior to pyramidal (PYR; i.e. greater volume in Z1 vs. Z2 vs. Z3) TID. The aim of the study was to compare the effect of POL vs. PYR TID in rowers during an 11-wk preparation period. Fourteen national elite male rowers participated (age: 20 ± 2 years, maximal oxygen uptake (⩒O2max): 66±5 mL/min/kg). The sample was split into PYR and POL by varying the percentage spent in Z2 and Z3 while Z1 was clamped to ~93% and matched for total and rowing volume. Actual TIDs were based on time within heart rate zones (Z1 and Z2) and duration of Z3-intervals. The main outcome variables were average power in 2000 m ergometer-test (P2000m), power associated with 4 mmol/L [blood lactate] (P4[BLa]), and ⩒O2max. To quantify the level of polarization, we calculated a Polarization-Index as log (%Z1 x %Z3/%Z2). PYR and POL did not significantly differ regarding rowing or total volume, but POL had a higher percentage of Z3 intensities (6±3% vs. 2±1%; p < .005) while Z2 was lower (1±1% vs. 3±2%; p < .05) and Z1 was similar (94±3% vs. 93±2%, p = .37). Consequently, Polarization-Index was significantly higher in POL (3.0±0.7 a.u. vs. 1.9±0.4 a.u.; p < .01) P2000m did not significantly change with PYR (1.5±1.7%, p = .06) nor POL (1.5±2.6%, p = .26). ⩒O2max did not change (1.7±5.6%, p = .52 or 0.6±2.6, p = .67) and a small increase in P4[BLa] was observed in PYR only (1.9±4.8%, p = .37 or -0.5±4.1%, p = .77). Changes from pre to post were not significantly different between groups in any performance measure. POL did not prove to be superior to PYR, possibly due to the high and very similar percentage of Z1 in this study.
  @article{treff2017elevenweek, abstract = {Polarized (POL) training intensity distribution (TID) emphasizes high-volume low-intensity exercise in zone (Z)1 (< first lactate threshold) with a greater proportion of high-intensity Z3 (> second lactate threshold) compared to Z2 (between first and second lactate threshold). In highly trained rowers there is a lack of prospective controlled evidence whether POL is superior to pyramidal (PYR; i.e. greater volume in Z1 vs. Z2 vs. Z3) TID. The aim of the study was to compare the effect of POL vs. PYR TID in rowers during an 11-wk preparation period. Fourteen national elite male rowers participated (age: 20 ± 2 years, maximal oxygen uptake (⩒O2max): 66±5 mL/min/kg). The sample was split into PYR and POL by varying the percentage spent in Z2 and Z3 while Z1 was clamped to &nbsp;93% and matched for total and rowing volume. Actual TIDs were based on time within heart rate zones (Z1 and Z2) and duration of Z3-intervals. The main outcome variables were average power in 2000 m ergometer-test (P2000m), power associated with 4 mmol/L [blood lactate] (P4[BLa]), and ⩒O2max. To quantify the level of polarization, we calculated a Polarization-Index as log (%Z1 x %Z3/%Z2). PYR and POL did not significantly differ regarding rowing or total volume, but POL had a higher percentage of Z3 intensities (6±3% vs. 2±1%; p < .005) while Z2 was lower (1±1% vs. 3±2%; p < .05) and Z1 was similar (94±3% vs. 93±2%, p = .37). Consequently, Polarization-Index was significantly higher in POL (3.0±0.7 a.u. vs. 1.9±0.4 a.u.; p < .01) P2000m did not significantly change with PYR (1.5±1.7%, p = .06) nor POL (1.5±2.6%, p = .26). ⩒O2max did not change (1.7±5.6%, p = .52 or 0.6±2.6, p = .67) and a small increase in P4[BLa] was observed in PYR only (1.9±4.8%, p = .37 or -0.5±4.1%, p = .77). Changes from pre to post were not significantly different between groups in any performance measure. POL did not prove to be superior to PYR, possibly due to the high and very similar percentage of Z1 in this study.}, author = {Treff, Gunnar and Winkert, Kay and Sareban, Mahdi and Steinacker, Jürgen M. and Becker, Martin and Sperlich, Billy}, journal = {Frontiers in Physiology}, keywords = {billy gunnar health heart hr myown rate row rower rowers rowing sports from:becker}, pages = 515, title = {Eleven-Week Preparation Involving Polarized Intensity Distribution Is Not Superior to Pyramidal Distribution in National Elite Rowers}, volume = 8, year = 2017 }
  %0 Journal Article %1 treff2017elevenweek %A Treff, Gunnar %A Winkert, Kay %A Sareban, Mahdi %A Steinacker, Jürgen M. %A Becker, Martin %A Sperlich, Billy %D 2017 %J Frontiers in Physiology %P 515 %R 10.3389/fphys.2017.00515 %T Eleven-Week Preparation Involving Polarized Intensity Distribution Is Not Superior to Pyramidal Distribution in National Elite Rowers %U http://journal.frontiersin.org/article/10.3389/fphys.2017.00515 %V 8 %X Polarized (POL) training intensity distribution (TID) emphasizes high-volume low-intensity exercise in zone (Z)1 (< first lactate threshold) with a greater proportion of high-intensity Z3 (> second lactate threshold) compared to Z2 (between first and second lactate threshold). In highly trained rowers there is a lack of prospective controlled evidence whether POL is superior to pyramidal (PYR; i.e. greater volume in Z1 vs. Z2 vs. Z3) TID. The aim of the study was to compare the effect of POL vs. PYR TID in rowers during an 11-wk preparation period. Fourteen national elite male rowers participated (age: 20 ± 2 years, maximal oxygen uptake (⩒O2max): 66±5 mL/min/kg). The sample was split into PYR and POL by varying the percentage spent in Z2 and Z3 while Z1 was clamped to ~93% and matched for total and rowing volume. Actual TIDs were based on time within heart rate zones (Z1 and Z2) and duration of Z3-intervals. The main outcome variables were average power in 2000 m ergometer-test (P2000m), power associated with 4 mmol/L [blood lactate] (P4[BLa]), and ⩒O2max. To quantify the level of polarization, we calculated a Polarization-Index as log (%Z1 x %Z3/%Z2). PYR and POL did not significantly differ regarding rowing or total volume, but POL had a higher percentage of Z3 intensities (6±3% vs. 2±1%; p < .005) while Z2 was lower (1±1% vs. 3±2%; p < .05) and Z1 was similar (94±3% vs. 93±2%, p = .37). Consequently, Polarization-Index was significantly higher in POL (3.0±0.7 a.u. vs. 1.9±0.4 a.u.; p < .01) P2000m did not significantly change with PYR (1.5±1.7%, p = .06) nor POL (1.5±2.6%, p = .26). ⩒O2max did not change (1.7±5.6%, p = .52 or 0.6±2.6, p = .67) and a small increase in P4[BLa] was observed in PYR only (1.9±4.8%, p = .37 or -0.5±4.1%, p = .77). Changes from pre to post were not significantly different between groups in any performance measure. POL did not prove to be superior to PYR, possibly due to the high and very similar percentage of Z1 in this study.
• 
  Flow-based benchmark data sets for intrusion detection. Ring, Markus; Wunderlich, Sarah; Grüdl, Dominik; Landes, Dieter; Hotho, Andreas (2017). 361--369.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{ring2017flow, author = {Ring, Markus and Wunderlich, Sarah and Gr{ü}dl, Dominik and Landes, Dieter and Hotho, Andreas}, booktitle = {Proceedings of the 16th European Conference on Cyber Warfare and Security}, keywords = {2017 benchmark citedby:scholar:count:4 citedby:scholar:timestamp:2018-1-31 detection flow from:hotho intrusion myown security}, pages = {361&ndash;369}, title = {Flow-based benchmark data sets for intrusion detection}, year = 2017 }
  %0 Conference Paper %1 ring2017flow %A Ring, Markus %A Wunderlich, Sarah %A Grüdl, Dominik %A Landes, Dieter %A Hotho, Andreas %B Proceedings of the 16th European Conference on Cyber Warfare and Security %D 2017 %P 361--369 %T Flow-based benchmark data sets for intrusion detection
• 
  Comparing Hypotheses About Sequential Data: A Bayesian Approach and Its Applications. Lemmerich, Florian; Singer, Philipp; Becker, Martin; Espin-Noboa, Lisette; Dimitrov, Dimitar; Helic, Denis; Hotho, Andreas; Strohmaier, Markus (2017). 354--357.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{lemmerich2017comparing, author = {Lemmerich, Florian and Singer, Philipp and Becker, Martin and Espin-Noboa, Lisette and Dimitrov, Dimitar and Helic, Denis and Hotho, Andreas and Strohmaier, Markus}, booktitle = {Joint European Conference on Machine Learning and Knowledge Discovery in Databases}, keywords = {bayes bayesian comparison data ecml hyptrails myown nectar sequential from:becker}, organization = {Springer}, pages = {354&ndash;357}, title = {Comparing Hypotheses About Sequential Data: A Bayesian Approach and Its Applications}, year = 2017 }
  %0 Conference Paper %1 lemmerich2017comparing %A Lemmerich, Florian %A Singer, Philipp %A Becker, Martin %A Espin-Noboa, Lisette %A Dimitrov, Dimitar %A Helic, Denis %A Hotho, Andreas %A Strohmaier, Markus %B Joint European Conference on Machine Learning and Knowledge Discovery in Databases %D 2017 %P 354--357 %T Comparing Hypotheses About Sequential Data: A Bayesian Approach and Its Applications
• 
  Creation of Flow-Based Data Sets for Intrusion Detection. Ring, Markus; Wunderlich, Sarah; Grüdl, Dominik; Landes, Dieter; Hotho, Andreas in Journal of Information Warfare (2017). 16(4) 41-54.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Publicly available labelled data sets are necessary for evaluating anomaly-based Intrusion Detection Systems (IDS). However, existing data sets are often not up-to-date or not yet published because of privacy concerns. This paper identifies requirements for good data sets and proposes an approach for their generation. The key idea is to use a test environment and emulate realistic user behaviour with parameterised scripts on the clients. Comprehensive logging mechanisms provide additional information which may be used for a better understanding of the inner dynamics of an IDS. Finally, the proposed approach is used to generate the flow-based CIDDS-002 data set.
  @article{ring2017creation, abstract = {Publicly available labelled data sets are necessary for evaluating anomaly-based Intrusion Detection Systems (IDS). However, existing data sets are often not up-to-date or not yet published because of privacy concerns. This paper identifies requirements for good data sets and proposes an approach for their generation. The key idea is to use a test environment and emulate realistic user behaviour with parameterised scripts on the clients. Comprehensive logging mechanisms provide additional information which may be used for a better understanding of the inner dynamics of an IDS. Finally, the proposed approach is used to generate the flow-based CIDDS-002 data set.}, author = {Ring, Markus and Wunderlich, Sarah and Grüdl, Dominik and Landes, Dieter and Hotho, Andreas}, journal = {Journal of Information Warfare}, keywords = {cidds from:markus0412 ids myown netflow openstack security security:selected}, month = {Dez}, number = 4, pages = {41-54}, title = {Creation of Flow-Based Data Sets for Intrusion Detection}, volume = 16, year = 2017 }
  %0 Journal Article %1 ring2017creation %A Ring, Markus %A Wunderlich, Sarah %A Grüdl, Dominik %A Landes, Dieter %A Hotho, Andreas %D 2017 %J Journal of Information Warfare %N 4 %P 41-54 %T Creation of Flow-Based Data Sets for Intrusion Detection %U https://www.jinfowar.com/journal/volume-16-issue-4/creation-flow-based-data-sets-intrusion-detection %V 16 %X Publicly available labelled data sets are necessary for evaluating anomaly-based Intrusion Detection Systems (IDS). However, existing data sets are often not up-to-date or not yet published because of privacy concerns. This paper identifies requirements for good data sets and proposes an approach for their generation. The key idea is to use a test environment and emulate realistic user behaviour with parameterised scripts on the clients. Comprehensive logging mechanisms provide additional information which may be used for a better understanding of the inner dynamics of an IDS. Finally, the proposed approach is used to generate the flow-based CIDDS-002 data set.
• 
  Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time. Dallmann, Alexander; Grimm, Alexander; Pölitz, Christian; Zoller, Daniel; Hotho, Andreas in CoRR (2017). abs/1706.10231
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @article{journals/corr/DallmannGPZH17, author = {Dallmann, Alexander and Grimm, Alexander and Pölitz, Christian and Zoller, Daniel and Hotho, Andreas}, journal = {CoRR}, keywords = {myown recommender research:recommender research:recommender:selected session}, title = {Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time.}, volume = {abs/1706.10231}, year = 2017 }
  %0 Journal Article %1 journals/corr/DallmannGPZH17 %A Dallmann, Alexander %A Grimm, Alexander %A Pölitz, Christian %A Zoller, Daniel %A Hotho, Andreas %D 2017 %J CoRR %T Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time. %U http://dblp.uni-trier.de/db/journals/corr/corr1706.html#DallmannGPZH17 %V abs/1706.10231
• 
  Sedentary Behavior among National Elite Rowers during Off-Training—A Pilot Study. Sperlich, Billy; Becker, Martin; Hotho, Andreas; Wallmann-Sperlich, Birgit; Sareban, Mahdi; Winkert, Kay; Steinacker, Jürgen M.; Treff, Gunnar in Frontiers in Physiology (2017). 8 655.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  The aim of this pilot study was to analyze the off-training physical activity (PA) profile in national elite German U23 rowers during 31 days of their preparation period. The hours spent in each PA category (i.e. sedentary: <1.5 MET; light physical activity: 1.5–3 MET; moderate physical activity: 3–6 MET and vigorous intense physical activity: >6 MET) were calculated for every valid day (i.e. > 480 min of wear time). The off-training PA during 21 weekdays and 10 weekend days of the final 11-wk preparation period was assessed by a wrist-worn multisensory device (Microsoft Band II (MSBII)). A total of 11 rowers provided valid data (i.e. > 480 min/day) for 11.6 week days and 4.8 weekend days during the 31 days observation period. The average sedentary time was 11.63±1.25 hours per day during the week and 12.49±1.10 hours per day on the weekend, with a tendency to be higher on the weekend compared to weekdays (p = 0.06; d = 0.73). The average time in light, moderate and vigorous PA during the weekdays was 1.27±1.15, 0.76±0.37, 0.51±0.44 hours per day and 0.67±0.43, 0.59±0.37, 0.53±0.32 hours per weekend day. Light physical activity was higher during weekdays compared to the weekend (p = 0.04; d = 0.69) Based on our pilot study of eleven national elite rowers we conclude that rowers display a considerable sedentary off-training behavior of more than 11.5 hours/day.
  @article{sperlich2017sedentary, abstract = {The aim of this pilot study was to analyze the off-training physical activity (PA) profile in national elite German U23 rowers during 31 days of their preparation period. The hours spent in each PA category (i.e. sedentary: <1.5 MET; light physical activity: 1.5–3 MET; moderate physical activity: 3–6 MET and vigorous intense physical activity: >6 MET) were calculated for every valid day (i.e. > 480 min of wear time). The off-training PA during 21 weekdays and 10 weekend days of the final 11-wk preparation period was assessed by a wrist-worn multisensory device (Microsoft Band II (MSBII)). A total of 11 rowers provided valid data (i.e. > 480 min/day) for 11.6 week days and 4.8 weekend days during the 31 days observation period. The average sedentary time was 11.63±1.25 hours per day during the week and 12.49±1.10 hours per day on the weekend, with a tendency to be higher on the weekend compared to weekdays (p = 0.06; d = 0.73). The average time in light, moderate and vigorous PA during the weekdays was 1.27±1.15, 0.76±0.37, 0.51±0.44 hours per day and 0.67±0.43, 0.59±0.37, 0.53±0.32 hours per weekend day. Light physical activity was higher during weekdays compared to the weekend (p = 0.04; d = 0.69) Based on our pilot study of eleven national elite rowers we conclude that rowers display a considerable sedentary off-training behavior of more than 11.5 hours/day.}, author = {Sperlich, Billy and Becker, Martin and Hotho, Andreas and Wallmann-Sperlich, Birgit and Sareban, Mahdi and Winkert, Kay and Steinacker, Jürgen M. and Treff, Gunnar}, journal = {Frontiers in Physiology}, keywords = {2 band behavior billy health microsoft msb myown national row rower rowing sendentary sport sports wearable from:becker}, pages = 655, title = {Sedentary Behavior among National Elite Rowers during Off-Training—A Pilot Study}, volume = 8, year = 2017 }
  %0 Journal Article %1 sperlich2017sedentary %A Sperlich, Billy %A Becker, Martin %A Hotho, Andreas %A Wallmann-Sperlich, Birgit %A Sareban, Mahdi %A Winkert, Kay %A Steinacker, Jürgen M. %A Treff, Gunnar %D 2017 %J Frontiers in Physiology %P 655 %R 10.3389/fphys.2017.00655 %T Sedentary Behavior among National Elite Rowers during Off-Training—A Pilot Study %U http://journal.frontiersin.org/article/10.3389/fphys.2017.00655 %V 8 %X The aim of this pilot study was to analyze the off-training physical activity (PA) profile in national elite German U23 rowers during 31 days of their preparation period. The hours spent in each PA category (i.e. sedentary: <1.5 MET; light physical activity: 1.5–3 MET; moderate physical activity: 3–6 MET and vigorous intense physical activity: >6 MET) were calculated for every valid day (i.e. > 480 min of wear time). The off-training PA during 21 weekdays and 10 weekend days of the final 11-wk preparation period was assessed by a wrist-worn multisensory device (Microsoft Band II (MSBII)). A total of 11 rowers provided valid data (i.e. > 480 min/day) for 11.6 week days and 4.8 weekend days during the 31 days observation period. The average sedentary time was 11.63±1.25 hours per day during the week and 12.49±1.10 hours per day on the weekend, with a tendency to be higher on the weekend compared to weekdays (p = 0.06; d = 0.73). The average time in light, moderate and vigorous PA during the weekdays was 1.27±1.15, 0.76±0.37, 0.51±0.44 hours per day and 0.67±0.43, 0.59±0.37, 0.53±0.32 hours per weekend day. Light physical activity was higher during weekdays compared to the weekend (p = 0.04; d = 0.69) Based on our pilot study of eleven national elite rowers we conclude that rowers display a considerable sedentary off-training behavior of more than 11.5 hours/day.
• 
  A Toolset for Intrusion and Insider Threat Detection. Ring, Markus; Wunderlich, Sarah; Grüdl, Dominik; Landes, Dieter; Hotho, Andreas in Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications, I. Palomares Carrascosa, Kalutarage, H. K., Huang, Y. (eds.) (2017). 3--31.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Company data are a valuable asset and must be protected against unauthorized access and manipulation. In this contribution, we report on our ongoing work that aims to support IT security experts with identifying novel or obfuscated attacks in company networks, irrespective of their origin inside or outside the company network. A new toolset for anomaly based network intrusion detection is proposed. This toolset uses flow-based data which can be easily retrieved by central network components. We study the challenges of analysing flow-based data streams using data mining algorithms and build an appropriate approach step by step. In contrast to previous work, we collect flow-based data for each host over a certain time window, include the knowledge of domain experts and analyse the data from three different views. We argue that incorporating expert knowledge and previous flows allow us to create more meaningful attributes for subsequent analysis methods. This way, we try to detect novel attacks while simultaneously limiting the number of false positives.
  @inbook{Ring2017, abstract = {Company data are a valuable asset and must be protected against unauthorized access and manipulation. In this contribution, we report on our ongoing work that aims to support IT security experts with identifying novel or obfuscated attacks in company networks, irrespective of their origin inside or outside the company network. A new toolset for anomaly based network intrusion detection is proposed. This toolset uses flow-based data which can be easily retrieved by central network components. We study the challenges of analysing flow-based data streams using data mining algorithms and build an appropriate approach step by step. In contrast to previous work, we collect flow-based data for each host over a certain time window, include the knowledge of domain experts and analyse the data from three different views. We argue that incorporating expert knowledge and previous flows allow us to create more meaningful attributes for subsequent analysis methods. This way, we try to detect novel attacks while simultaneously limiting the number of false positives.}, address = {Cham}, author = {Ring, Markus and Wunderlich, Sarah and Gr{ü}dl, Dominik and Landes, Dieter and Hotho, Andreas}, booktitle = {Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications}, editor = {Palomares Carrascosa, Iv{á}n and Kalutarage, Harsha Kumara and Huang, Yan}, keywords = {from:markus0412 intrusion myown security security:selected}, pages = {3&ndash;31}, publisher = {Springer International Publishing}, title = {A Toolset for Intrusion and Insider Threat Detection}, year = 2017 }
  %0 Book Section %1 Ring2017 %A Ring, Markus %A Wunderlich, Sarah %A Grüdl, Dominik %A Landes, Dieter %A Hotho, Andreas %B Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications %C Cham %D 2017 %E Palomares Carrascosa, Iván %E Kalutarage, Harsha Kumara %E Huang, Yan %I Springer International Publishing %P 3--31 %R 10.1007/978-3-319-59439-2_1 %T A Toolset for Intrusion and Insider Threat Detection %U https://doi.org/10.1007/978-3-319-59439-2_1 %X Company data are a valuable asset and must be protected against unauthorized access and manipulation. In this contribution, we report on our ongoing work that aims to support IT security experts with identifying novel or obfuscated attacks in company networks, irrespective of their origin inside or outside the company network. A new toolset for anomaly based network intrusion detection is proposed. This toolset uses flow-based data which can be easily retrieved by central network components. We study the challenges of analysing flow-based data streams using data mining algorithms and build an appropriate approach step by step. In contrast to previous work, we collect flow-based data for each host over a certain time window, include the knowledge of domain experts and analyse the data from three different views. We argue that incorporating expert knowledge and previous flows allow us to create more meaningful attributes for subsequent analysis methods. This way, we try to detect novel attacks while simultaneously limiting the number of false positives. %@ 978-3-319-59439-2
• 
  Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning. Niebler, Thomas; Becker, Martin; Pölitz, Christian; Hotho, Andreas (2017).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{niebler2017learning_3, author = {Niebler, Thomas and Becker, Martin and Pölitz, Christian and Hotho, Andreas}, booktitle = {ISWC'17}, keywords = {feedback from:thoni human learning myown posts postsii project:bibsonomy relatedness relative selected semantic semantic:selected semantics}, title = {Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning}, year = 2017 }
  %0 Conference Paper %1 niebler2017learning_3 %A Niebler, Thomas %A Becker, Martin %A Pölitz, Christian %A Hotho, Andreas %B ISWC'17 %D 2017 %T Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning
• 
  Towards Sentiment Analysis on German Literature. Zehe, Albin; Becker, Martin; Jannidis, Fotis; Hotho, Andreas (2017).
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  @inproceedings{zehe2017sentiment, author = {Zehe, Albin and Becker, Martin and Jannidis, Fotis and Hotho, Andreas}, keywords = {cnn dh from:albinzehe kallimachos ma-zehe myown neuralnet sentimentanalysis}, title = {Towards Sentiment Analysis on German Literature}, year = 2017 }
  %0 Conference Paper %1 zehe2017sentiment %A Zehe, Albin %A Becker, Martin %A Jannidis, Fotis %A Hotho, Andreas %D 2017 %T Towards Sentiment Analysis on German Literature
• 
  A Bayesian Method for Comparing Hypotheses About Human Trails. Singer, Philipp; Helic, Denis; Hotho, Andreas; Strohmaier, Markus in ACM Trans. Web (2017). 11(3) 14:1--14:29.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful, for example, for improving underlying network structures, predicting user clicks, or enhancing recommendations. In this work, we present a method called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our method utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to calculate the evidence of the data under them. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method, and to compare the relative plausibility of hypotheses, we employ Bayes factors. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including Web site navigation, business reviews, and online music played. Our work expands the repertoire of methods available for studying human trails.
  @article{singer2017bayesian, abstract = {When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful, for example, for improving underlying network structures, predicting user clicks, or enhancing recommendations. In this work, we present a method called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our method utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to calculate the evidence of the data under them. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method, and to compare the relative plausibility of hypotheses, we employ Bayes factors. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including Web site navigation, business reviews, and online music played. Our work expands the repertoire of methods available for studying human trails.}, address = {New York, NY, USA}, author = {Singer, Philipp and Helic, Denis and Hotho, Andreas and Strohmaier, Markus}, journal = {ACM Trans. Web}, keywords = {2017 from:hotho hyptrails long myown tweb version}, month = {jun}, number = 3, pages = {14:1&ndash;14:29}, publisher = {ACM}, title = {A Bayesian Method for Comparing Hypotheses About Human Trails}, volume = 11, year = 2017 }
  %0 Journal Article %1 singer2017bayesian %A Singer, Philipp %A Helic, Denis %A Hotho, Andreas %A Strohmaier, Markus %C New York, NY, USA %D 2017 %I ACM %J ACM Trans. Web %N 3 %P 14:1--14:29 %R 10.1145/3054950 %T A Bayesian Method for Comparing Hypotheses About Human Trails %U http://doi.acm.org/10.1145/3054950 %V 11 %X When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful, for example, for improving underlying network structures, predicting user clicks, or enhancing recommendations. In this work, we present a method called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our method utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to calculate the evidence of the data under them. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method, and to compare the relative plausibility of hypotheses, we employ Bayes factors. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including Web site navigation, business reviews, and online music played. Our work expands the repertoire of methods available for studying human trails.
• 
  Participatory sensing, opinions and collective awareness Loreto, Vittorio; Haklay, Mordechai; Hotho, Andreas; Servedio, Vito C. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca (2017). Springer.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @book{loreto2017participatory, editor = {Loreto, Vittorio and Haklay, Mordechai and Hotho, Andreas and Servedio, Vito C. P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca}, keywords = {environmental environmental:selected everyaware myown participatory sensing}, publisher = {Springer}, title = {Participatory sensing, opinions and collective awareness}, year = 2017 }
  %0 Book %1 loreto2017participatory %D 2017 %E Loreto, Vittorio %E Haklay, Mordechai %E Hotho, Andreas %E Servedio, Vito C. P. %E Stumme, Gerd %E Theunis, Jan %E Tria, Francesca %I Springer %T Participatory sensing, opinions and collective awareness %@ 9783319256580 3319256580
• 
  Applications for Environmental Sensing in EveryAware. Atzmueller, Martin; Becker, Martin; Molino, Andrea; Mueller, Juergen; Peters, Jan; S^irbu, Alina in Participatory Sensing, Opinions and Collective Awareness (2017). 135--155.
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  @incollection{atzmueller2017applications, author = {Atzmueller, Martin and Becker, Martin and Molino, Andrea and Mueller, Juergen and Peters, Jan and S{\^\i}rbu, Alina}, booktitle = {Participatory Sensing, Opinions and Collective Awareness}, keywords = {behavior book chapter drift environment environmental everyaware from:becker myown opinion participatory sensing}, pages = {135&ndash;155}, publisher = {Springer}, title = {Applications for Environmental Sensing in EveryAware}, year = 2017 }
  %0 Book Section %1 atzmueller2017applications %A Atzmueller, Martin %A Becker, Martin %A Molino, Andrea %A Mueller, Juergen %A Peters, Jan %A S^irbu, Alina %B Participatory Sensing, Opinions and Collective Awareness %D 2017 %I Springer %P 135--155 %T Applications for Environmental Sensing in EveryAware
• 
  Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson. Gravino, Pietro; S^irbu, Alina; Becker, Martin; Servedio, Vito DP; Loreto, Vittorio in Participatory Sensing, Opinions and Collective Awareness (2017). 337--362.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @incollection{gravino2017experimental, author = {Gravino, Pietro and S{\^\i}rbu, Alina and Becker, Martin and Servedio, Vito DP and Loreto, Vittorio}, booktitle = {Participatory Sensing, Opinions and Collective Awareness}, keywords = {environmental everyaware from:becker myown}, pages = {337&ndash;362}, publisher = {Springer}, title = {Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson}, year = 2017 }
  %0 Book Section %1 gravino2017experimental %A Gravino, Pietro %A S^irbu, Alina %A Becker, Martin %A Servedio, Vito DP %A Loreto, Vittorio %B Participatory Sensing, Opinions and Collective Awareness %D 2017 %I Springer %P 337--362 %T Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson
• 
  Collective Sensing Platforms. Atzmueller, Martin; Becker, Martin; Mueller, Juergen in Participatory Sensing, Opinions and Collective Awareness (2017). 115--133.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @incollection{atzmueller2017collective, author = {Atzmueller, Martin and Becker, Martin and Mueller, Juergen}, booktitle = {Participatory Sensing, Opinions and Collective Awareness}, keywords = {environmental environmental:selected everyaware from:becker myown}, pages = {115&ndash;133}, publisher = {Springer}, title = {Collective Sensing Platforms}, year = 2017 }
  %0 Book Section %1 atzmueller2017collective %A Atzmueller, Martin %A Becker, Martin %A Mueller, Juergen %B Participatory Sensing, Opinions and Collective Awareness %D 2017 %I Springer %P 115--133 %T Collective Sensing Platforms
• 
  Mining social semantics on the social web. Hotho, A.; Jaeschke, R.; Lerman, K. in Semantic Web (2017). 8(5) 623--624.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @article{wrro115871, author = {Hotho, A. and Jaeschke, R. and Lerman, K.}, journal = {Semantic Web}, keywords = {2017 mining myown semantic social web from:hotho}, month = {April}, note = {\copyright 2017 IOS Press and the authors. This is an author produced version of a paper subsequently published in Semantic Web. Uploaded in accordance with the publisher's self-archiving policy.}, number = 5, pages = {623&ndash;624}, publisher = {IOS Press}, title = {Mining social semantics on the social web}, volume = 8, year = 2017 }
  %0 Journal Article %1 wrro115871 %A Hotho, A. %A Jaeschke, R. %A Lerman, K. %D 2017 %I IOS Press %J Semantic Web %N 5 %P 623--624 %T Mining social semantics on the social web %U http://eprints.whiterose.ac.uk/115871/ %V 8
• 
  Learning Semantic Relatedness From Human Feedback Using Metric Learning. Niebler, Thomas; Becker, Martin; Pölitz, Christian; Hotho, Andreas (2017).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Assessing the degree of semantic relatedness between words is an important task with a variety of semantic applications, such as ontology learning for the Semantic Web, semantic search or query expansion. To accomplish this in an automated fashion, many relatedness measures have been proposed. However, most of these metrics only encode information contained in the underlying corpus and thus do not directly model human intuition. To solve this, we propose to utilize a metric learning approach to improve existing semantic relatedness measures by learning from additional information, such as explicit human feedback. For this, we argue to use word embeddings instead of traditional high-dimensional vector representations in order to leverage their semantic density and to reduce computational cost. We rigorously test our approach on several domains including tagging data as well as publicly available embeddings based on Wikipedia texts and navigation. Human feedback about semantic relatedness for learning and evaluation is extracted from publicly available datasets such as MEN or WS-353. We find that our method can significantly improve semantic relatedness measures by learning from additional information, such as explicit human feedback. For tagging data, we are the first to generate and study embeddings. Our results are of special interest for ontology and recommendation engineers, but also for any other researchers and practitioners of Semantic Web techniques.
  @misc{niebler2017learning, abstract = {Assessing the degree of semantic relatedness between words is an important task with a variety of semantic applications, such as ontology learning for the Semantic Web, semantic search or query expansion. To accomplish this in an automated fashion, many relatedness measures have been proposed. However, most of these metrics only encode information contained in the underlying corpus and thus do not directly model human intuition. To solve this, we propose to utilize a metric learning approach to improve existing semantic relatedness measures by learning from additional information, such as explicit human feedback. For this, we argue to use word embeddings instead of traditional high-dimensional vector representations in order to leverage their semantic density and to reduce computational cost. We rigorously test our approach on several domains including tagging data as well as publicly available embeddings based on Wikipedia texts and navigation. Human feedback about semantic relatedness for learning and evaluation is extracted from publicly available datasets such as MEN or WS-353. We find that our method can significantly improve semantic relatedness measures by learning from additional information, such as explicit human feedback. For tagging data, we are the first to generate and study embeddings. Our results are of special interest for ontology and recommendation engineers, but also for any other researchers and practitioners of Semantic Web techniques.}, author = {Niebler, Thomas and Becker, Martin and Pölitz, Christian and Hotho, Andreas}, keywords = {learning metric myown posts postsii relatedness semantic from:thoni}, note = {cite arxiv:1705.07425}, title = {Learning Semantic Relatedness From Human Feedback Using Metric Learning}, year = 2017 }
  %0 Generic %1 niebler2017learning %A Niebler, Thomas %A Becker, Martin %A Pölitz, Christian %A Hotho, Andreas %D 2017 %T Learning Semantic Relatedness From Human Feedback Using Metric Learning %U http://arxiv.org/abs/1705.07425 %X Assessing the degree of semantic relatedness between words is an important task with a variety of semantic applications, such as ontology learning for the Semantic Web, semantic search or query expansion. To accomplish this in an automated fashion, many relatedness measures have been proposed. However, most of these metrics only encode information contained in the underlying corpus and thus do not directly model human intuition. To solve this, we propose to utilize a metric learning approach to improve existing semantic relatedness measures by learning from additional information, such as explicit human feedback. For this, we argue to use word embeddings instead of traditional high-dimensional vector representations in order to leverage their semantic density and to reduce computational cost. We rigorously test our approach on several domains including tagging data as well as publicly available embeddings based on Wikipedia texts and navigation. Human feedback about semantic relatedness for learning and evaluation is extracted from publicly available datasets such as MEN or WS-353. We find that our method can significantly improve semantic relatedness measures by learning from additional information, such as explicit human feedback. For tagging data, we are the first to generate and study embeddings. Our results are of special interest for ontology and recommendation engineers, but also for any other researchers and practitioners of Semantic Web techniques.
• 
  MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data. Becker, Martin; Lemmerich, Florian; Singer, Philipp; Strohmaier, Markus; Hotho, Andreas in Data Mining and Knowledge Discovery (2017).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Sequential traces of user data are frequently observed online and offline, e.g., as sequences of visited websites or as sequences of locations captured by GPS. However, understanding factors explaining the production of sequence data is a challenging task, especially since the data generation is often not homogeneous. For example, navigation behavior might change in different phases of browsing a website or movement behavior may vary between groups of users. In this work, we tackle this task and propose MixedTrails , a Bayesian approach for comparing the plausibility of hypotheses regarding the generative processes of heterogeneous sequence data. Each hypothesis is derived from existing literature, theory, or intuition and represents a belief about transition probabilities between a set of states that can vary between groups of observed transitions. For example, when trying to understand human movement in a city and given some data, a hypothesis assuming tourists to be more likely to move towards points of interests than locals can be shown to be more plausible than a hypothesis assuming the opposite. Our approach incorporates such hypotheses as Bayesian priors in a generative mixed transition Markov chain model, and compares their plausibility utilizing Bayes factors. We discuss analytical and approximate inference methods for calculating the marginal likelihoods for Bayes factors, give guidance on interpreting the results, and illustrate our approach with several experiments on synthetic and empirical data from Wikipedia and Flickr. Thus, this work enables a novel kind of analysis for studying sequential data in many application areas.
  @article{becker2017mixedtrails, abstract = {Sequential traces of user data are frequently observed online and offline, e.g., as sequences of visited websites or as sequences of locations captured by GPS. However, understanding factors explaining the production of sequence data is a challenging task, especially since the data generation is often not homogeneous. For example, navigation behavior might change in different phases of browsing a website or movement behavior may vary between groups of users. In this work, we tackle this task and propose MixedTrails , a Bayesian approach for comparing the plausibility of hypotheses regarding the generative processes of heterogeneous sequence data. Each hypothesis is derived from existing literature, theory, or intuition and represents a belief about transition probabilities between a set of states that can vary between groups of observed transitions. For example, when trying to understand human movement in a city and given some data, a hypothesis assuming tourists to be more likely to move towards points of interests than locals can be shown to be more plausible than a hypothesis assuming the opposite. Our approach incorporates such hypotheses as Bayesian priors in a generative mixed transition Markov chain model, and compares their plausibility utilizing Bayes factors. We discuss analytical and approximate inference methods for calculating the marginal likelihoods for Bayes factors, give guidance on interpreting the results, and illustrate our approach with several experiments on synthetic and empirical data from Wikipedia and Flickr. Thus, this work enables a novel kind of analysis for studying sequential data in many application areas.}, author = {Becker, Martin and Lemmerich, Florian and Singer, Philipp and Strohmaier, Markus and Hotho, Andreas}, journal = {Data Mining and Knowledge Discovery}, keywords = {bayesian behavior comparison data from:becker heterogeneous human mixedtrails model myown navigation navigational posts postsii project:p2map selected sequence}, month = {jul}, title = {MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data}, year = 2017 }
  %0 Journal Article %1 becker2017mixedtrails %A Becker, Martin %A Lemmerich, Florian %A Singer, Philipp %A Strohmaier, Markus %A Hotho, Andreas %D 2017 %J Data Mining and Knowledge Discovery %R 10.1007/s10618-017-0518-x %T MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data %U http://dx.doi.org/10.1007/s10618-017-0518-x %X Sequential traces of user data are frequently observed online and offline, e.g., as sequences of visited websites or as sequences of locations captured by GPS. However, understanding factors explaining the production of sequence data is a challenging task, especially since the data generation is often not homogeneous. For example, navigation behavior might change in different phases of browsing a website or movement behavior may vary between groups of users. In this work, we tackle this task and propose MixedTrails , a Bayesian approach for comparing the plausibility of hypotheses regarding the generative processes of heterogeneous sequence data. Each hypothesis is derived from existing literature, theory, or intuition and represents a belief about transition probabilities between a set of states that can vary between groups of observed transitions. For example, when trying to understand human movement in a city and given some data, a hypothesis assuming tourists to be more likely to move towards points of interests than locals can be shown to be more plausible than a hypothesis assuming the opposite. Our approach incorporates such hypotheses as Bayesian priors in a generative mixed transition Markov chain model, and compares their plausibility utilizing Bayes factors. We discuss analytical and approximate inference methods for calculating the marginal likelihoods for Bayes factors, give guidance on interpreting the results, and illustrate our approach with several experiments on synthetic and empirical data from Wikipedia and Flickr. Thus, this work enables a novel kind of analysis for studying sequential data in many application areas.
• 
  Learning Word Embeddings from Tagging Data: A methodological comparison. Niebler, Thomas; Hahn, Luzian; Hotho, Andreas (2017).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{niebler2017learning_2, author = {Niebler, Thomas and Hahn, Luzian and Hotho, Andreas}, booktitle = {Proceedings of the LWDA}, keywords = {bibsonomy citeulike delicious embeddings from:thoni glove line myown semantic tag word2vec}, title = {Learning Word Embeddings from Tagging Data: A methodological comparison}, year = 2017 }
  %0 Conference Paper %1 niebler2017learning_2 %A Niebler, Thomas %A Hahn, Luzian %A Hotho, Andreas %B Proceedings of the LWDA %D 2017 %T Learning Word Embeddings from Tagging Data: A methodological comparison
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  IP2Vec: Learning Similarities Between IP Addresses. Ring, Markus; Landes, Dieter; Dallmann, Alexander; Hotho, Andreas in 2017 IEEE International Conference on Data Mining Workshops (ICDMW) (2017). 657-666.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @article{ring2017ip2vec, author = {Ring, Markus and Landes, Dieter and Dallmann, Alexander and Hotho, Andreas}, journal = {2017 IEEE International Conference on Data Mining Workshops (ICDMW)}, keywords = {2017 distance from:hotho ip ip2vec myown security:selected similarity}, pages = {657-666}, title = {IP2Vec: Learning Similarities Between IP Addresses}, type = {Publication}, year = 2017 }
  %0 Journal Article %1 ring2017ip2vec %A Ring, Markus %A Landes, Dieter %A Dallmann, Alexander %A Hotho, Andreas %D 2017 %J 2017 IEEE International Conference on Data Mining Workshops (ICDMW) %P 657-666 %R 10.1109/ICDMW.2017.93 %T IP2Vec: Learning Similarities Between IP Addresses %@ 978-1-5386-3800-2

2016 [ to top ]

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  Mining Subgroups with Exceptional Transition Behavior. Lemmerich, Florian; Becker, Martin; Singer, Philipp; Helic, Denis; Hotho, Andreas; Strohmaier, Markus B. Krishnapuram, Shah, M., Smola, A. J., Aggarwal, C., Shen, D., Rastogi, R. (eds.) (2016). 965-974.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{lemmerich2016mining, author = {Lemmerich, Florian and Becker, Martin and Singer, Philipp and Helic, Denis and Hotho, Andreas and Strohmaier, Markus}, booktitle = {KDD}, crossref = {conf/kdd/2016}, editor = {Krishnapuram, Balaji and Shah, Mohak and Smola, Alexander J. and Aggarwal, Charu and Shen, Dou and Rastogi, Rajeev}, keywords = {bayesian bmbf discovery erp from:becker hyptrails myown posts postsII pv selected subgroup subtrails}, pages = {965-974}, publisher = {ACM}, title = {Mining Subgroups with Exceptional Transition Behavior.}, year = 2016 }
  %0 Conference Paper %1 lemmerich2016mining %A Lemmerich, Florian %A Becker, Martin %A Singer, Philipp %A Helic, Denis %A Hotho, Andreas %A Strohmaier, Markus %B KDD %D 2016 %E Krishnapuram, Balaji %E Shah, Mohak %E Smola, Alexander J. %E Aggarwal, Charu %E Shen, Dou %E Rastogi, Rajeev %I ACM %P 965-974 %T Mining Subgroups with Exceptional Transition Behavior. %U http://dblp.uni-trier.de/db/conf/kdd/kdd2016.html#Lemmerich0SHHS16 %@ 978-1-4503-4232-2
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  FolkTrails: Interpreting Navigation Behavior in a Social Tagging System. Niebler, Thomas; Becker, Martin; Zoller, Daniel; Doerfel, Stephan; Hotho, Andreas in CIKM '16 (2016).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.
  @inproceedings{niebler2016folktrails, abstract = {Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.}, address = {New York, NY, USA}, author = {Niebler, Thomas and Becker, Martin and Zoller, Daniel and Doerfel, Stephan and Hotho, Andreas}, booktitle = {Proceedings of the 25th ACM International on Conference on Information and Knowledge Management}, keywords = {behavior bibsonomy bibsonomy:selected folktrails from:nosebrain hyptrails myown navigation posts postsII project:bibsonomy semantic social system tagging}, publisher = {ACM}, series = {CIKM '16}, title = {FolkTrails: Interpreting Navigation Behavior in a Social Tagging System}, year = 2016 }
  %0 Conference Paper %1 niebler2016folktrails %A Niebler, Thomas %A Becker, Martin %A Zoller, Daniel %A Doerfel, Stephan %A Hotho, Andreas %B Proceedings of the 25th ACM International on Conference on Information and Knowledge Management %C New York, NY, USA %D 2016 %I ACM %R 10.1145/2983323.2983686 %T FolkTrails: Interpreting Navigation Behavior in a Social Tagging System %X Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.
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  SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails. Becker, Martin; Mewes, Hauke; Hotho, Andreas; Dimitrov, Dimitar; Lemmerich, Florian; Strohmaier, Markus J. Bourdeau, Hendler, J., Nkambou, R., Horrocks, I., Zhao, B. Y. (eds.) (2016). 17-18.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{becker2016sparktrails, author = {Becker, Martin and Mewes, Hauke and Hotho, Andreas and Dimitrov, Dimitar and Lemmerich, Florian and Strohmaier, Markus}, booktitle = {WWW (Companion Volume)}, crossref = {conf/www/2016c}, editor = {Bourdeau, Jacqueline and Hendler, Jim and Nkambou, Roger and Horrocks, Ian and Zhao, Ben Y.}, keywords = {bayes bayesian comparison factor from:becker hypothesis hyptrails movement myown pattern posts postsii selected}, pages = {17-18}, publisher = {ACM}, title = {SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails.}, year = 2016 }
  %0 Conference Paper %1 becker2016sparktrails %A Becker, Martin %A Mewes, Hauke %A Hotho, Andreas %A Dimitrov, Dimitar %A Lemmerich, Florian %A Strohmaier, Markus %B WWW (Companion Volume) %D 2016 %E Bourdeau, Jacqueline %E Hendler, Jim %E Nkambou, Roger %E Horrocks, Ian %E Zhao, Ben Y. %I ACM %P 17-18 %T SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails. %U http://dblp.uni-trier.de/db/conf/www/www2016c.html#0003MHDLS16 %@ 978-1-4503-4144-8
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  Prediction of Happy Endings in German Novels. Zehe, Albin; Becker, Martin; Hettinger, Lena; Hotho, Andreas; Reger, Isabella; Jannidis, Fotis P. Cellier, Charnois, T., Hotho, A., Matwin, S., Moens, M. -F., Toussaint, Y. (eds.) (2016). 9-16.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Identifying plot structure in novels is a valuable step towards automatic processing of literary corpora. We present an approach to classify novels as either having a happy ending or not. To achieve this, we use features based on different sentiment lexica as input for an SVM- classifier, which yields an average F1-score of about 73%.
  @inproceedings{zehe2016prediction, abstract = {Identifying plot structure in novels is a valuable step towards automatic processing of literary corpora. We present an approach to classify novels as either having a happy ending or not. To achieve this, we use features based on different sentiment lexica as input for an SVM- classifier, which yields an average F1-score of about 73%.}, author = {Zehe, Albin and Becker, Martin and Hettinger, Lena and Hotho, Andreas and Reger, Isabella and Jannidis, Fotis}, booktitle = {Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing 2016}, editor = {Cellier, Peggy and Charnois, Thierry and Hotho, Andreas and Matwin, Stan and Moens, Marie-Francine and Toussaint, Yannick}, keywords = {analysis dh endings from:schwemmlein happy kallimachos myown novels sentiment}, month = {jul}, pages = {9-16}, title = {Prediction of Happy Endings in German Novels}, year = 2016 }
  %0 Conference Paper %1 zehe2016prediction %A Zehe, Albin %A Becker, Martin %A Hettinger, Lena %A Hotho, Andreas %A Reger, Isabella %A Jannidis, Fotis %B Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing 2016 %D 2016 %E Cellier, Peggy %E Charnois, Thierry %E Hotho, Andreas %E Matwin, Stan %E Moens, Marie-Francine %E Toussaint, Yannick %P 9-16 %T Prediction of Happy Endings in German Novels %U http://ceur-ws.org/Vol-1646/ %X Identifying plot structure in novels is a valuable step towards automatic processing of literary corpora. We present an approach to classify novels as either having a happy ending or not. To achieve this, we use features based on different sentiment lexica as input for an SVM- classifier, which yields an average F1-score of about 73%.
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  Extracting Semantics from Unconstrained Navigation on Wikipedia. Niebler, Thomas; Schlör, Daniel; Becker, Martin; Hotho, Andreas in KI (2016). 30(2) 163-168.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @article{journals/ki/NieblerS0H16, author = {Niebler, Thomas and Schlör, Daniel and Becker, Martin and Hotho, Andreas}, journal = {KI}, keywords = {2015 2016 behaviour extracting extraction from:hotho log myown navigation posts postsII relatedness selected semantic semantic:selected user wikipedia}, number = 2, pages = {163-168}, title = {Extracting Semantics from Unconstrained Navigation on Wikipedia}, volume = 30, year = 2016 }
  %0 Journal Article %1 journals/ki/NieblerS0H16 %A Niebler, Thomas %A Schlör, Daniel %A Becker, Martin %A Hotho, Andreas %D 2016 %J KI %N 2 %P 163-168 %T Extracting Semantics from Unconstrained Navigation on Wikipedia %U http://dblp.uni-trier.de/db/journals/ki/ki30.html#NieblerS0H16 %V 30
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  Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies. Düking, Peter; Hotho, Andreas; Fuss, Franz Konstantin; Holmberg, Hans-Christer; Sperlich, Billy in Frontiers in Physiology (2016). 7(71)
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Athletes adapt their training daily to optimize performance, as well as avoid fatigue, overtraining and other undesirable effects on their health. To optimize training load, each athlete must take his/her own personal objective and subjective characteristics into consideration and an increasing number of wearable technologies (wearables) provide convenient monitoring of various parameters. Accordingly, it is important to help athletes decide which parameters are of primary interest and which wearables can monitor these parameters most effectively. Here, we discuss the wearable technologies available for non-invasive monitoring of various parameters concerning an athlete's training and health. On the basis of these considerations, we suggest directions for future development. Furthermore, we propose that a combination of several wearables is most effective for accessing all relevant parameters, disturbing the athlete as little as possible, and optimizing performance and promoting health.
  @article{10.3389/fphys.2016.00071, abstract = {Athletes adapt their training daily to optimize performance, as well as avoid fatigue, overtraining and other undesirable effects on their health. To optimize training load, each athlete must take his/her own personal objective and subjective characteristics into consideration and an increasing number of wearable technologies (wearables) provide convenient monitoring of various parameters. Accordingly, it is important to help athletes decide which parameters are of primary interest and which wearables can monitor these parameters most effectively. Here, we discuss the wearable technologies available for non-invasive monitoring of various parameters concerning an athlete's training and health. On the basis of these considerations, we suggest directions for future development. Furthermore, we propose that a combination of several wearables is most effective for accessing all relevant parameters, disturbing the athlete as little as possible, and optimizing performance and promoting health.}, author = {Düking, Peter and Hotho, Andreas and Fuss, Franz Konstantin and Holmberg, Hans-Christer and Sperlich, Billy}, journal = {Frontiers in Physiology}, keywords = {compare data fitness from:hotho myown sport wearable}, number = 71, title = {Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies}, volume = 7, year = 2016 }
  %0 Journal Article %1 10.3389/fphys.2016.00071 %A Düking, Peter %A Hotho, Andreas %A Fuss, Franz Konstantin %A Holmberg, Hans-Christer %A Sperlich, Billy %D 2016 %J Frontiers in Physiology %N 71 %R 10.3389/fphys.2016.00071 %T Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies %U http://www.frontiersin.org/exercise_physiology/10.3389/fphys.2016.00071/abstract %V 7 %X Athletes adapt their training daily to optimize performance, as well as avoid fatigue, overtraining and other undesirable effects on their health. To optimize training load, each athlete must take his/her own personal objective and subjective characteristics into consideration and an increasing number of wearable technologies (wearables) provide convenient monitoring of various parameters. Accordingly, it is important to help athletes decide which parameters are of primary interest and which wearables can monitor these parameters most effectively. Here, we discuss the wearable technologies available for non-invasive monitoring of various parameters concerning an athlete's training and health. On the basis of these considerations, we suggest directions for future development. Furthermore, we propose that a combination of several wearables is most effective for accessing all relevant parameters, disturbing the athlete as little as possible, and optimizing performance and promoting health.
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  Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy. Zoller, Daniel; Doerfel, Stephan; Jäschke, Robert; Stumme, Gerd; Hotho, Andreas in Journal of Informetrics (2016). 10(3) 732--749.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.
  @article{zoller2016posted, abstract = {In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.}, author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas}, journal = {Journal of Informetrics}, keywords = {altmetrics analysis bibsonomy:selected from:nosebrain log myown project:bibsonomy selected social tagging}, number = 3, pages = {732&ndash;749}, title = {Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy}, volume = 10, year = 2016 }
  %0 Journal Article %1 zoller2016posted %A Zoller, Daniel %A Doerfel, Stephan %A Jäschke, Robert %A Stumme, Gerd %A Hotho, Andreas %D 2016 %J Journal of Informetrics %N 3 %P 732--749 %T Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy %V 10 %X In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.
• 
  MixedTrails: Bayesian Hypotheses Comparison on Heterogeneous Sequential Data. Becker, Martin; Lemmerich, Florian; Singer, Philipp; Strohmaier, Markus; Hotho, Andreas (2016).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Sequential traces of user data are frequently observed online and offline, e.g.,as sequences of visited websites or as sequences of locations captured by GPS. However,understanding factors explaining the production of sequence data is a challenging task,especially since the data generation is often not homogeneous. For example, navigation behavior might change in different phases of a website visit, or movement behavior may vary between groups of user. In this work, we tackle this task and propose MixedTrails, a Bayesian approach for comparing the plausibility of hypotheses regarding the generative processes of heterogeneous sequence data. Each hypothesis represents a belief about transition probabilities between a set of states that can vary between groups of observed transitions.For example, when trying to understand human movement in a city, a hypothesis assuming tourists to be more likely to move towards points of interests than locals, can be shown to be more plausible with observed data than a hypothesis assuming the opposite. Our approach incorporates these beliefs as Bayesian priors in a generative mixed transition Markov chain model, and compares their plausibility utilizing Bayes factors. We discuss analytical and approximate inference methods for calculating the marginal likelihoods for Bayes factors,give guidance on interpreting the results, and illustrate our approach with several experiments on synthetic and empirical data from Wikipedia and Flickr. Thus, this work enables a novel kind of analysis for studying sequential data in many application areas.
  @misc{becker2016mixedtrails, abstract = {Sequential traces of user data are frequently observed online and offline, e.g.,as sequences of visited websites or as sequences of locations captured by GPS. However,understanding factors explaining the production of sequence data is a challenging task,especially since the data generation is often not homogeneous. For example, navigation behavior might change in different phases of a website visit, or movement behavior may vary between groups of user. In this work, we tackle this task and propose MixedTrails, a Bayesian approach for comparing the plausibility of hypotheses regarding the generative processes of heterogeneous sequence data. Each hypothesis represents a belief about transition probabilities between a set of states that can vary between groups of observed transitions.For example, when trying to understand human movement in a city, a hypothesis assuming tourists to be more likely to move towards points of interests than locals, can be shown to be more plausible with observed data than a hypothesis assuming the opposite. Our approach incorporates these beliefs as Bayesian priors in a generative mixed transition Markov chain model, and compares their plausibility utilizing Bayes factors. We discuss analytical and approximate inference methods for calculating the marginal likelihoods for Bayes factors,give guidance on interpreting the results, and illustrate our approach with several experiments on synthetic and empirical data from Wikipedia and Flickr. Thus, this work enables a novel kind of analysis for studying sequential data in many application areas.}, author = {Becker, Martin and Lemmerich, Florian and Singer, Philipp and Strohmaier, Markus and Hotho, Andreas}, keywords = {bayes comparison data factor from:becker hypothesis hyptrails mixedtrails myown selected sequential}, note = {cite arxiv:1612.07612}, title = {MixedTrails: Bayesian Hypotheses Comparison on Heterogeneous Sequential Data}, year = 2016 }
  %0 Generic %1 becker2016mixedtrails %A Becker, Martin %A Lemmerich, Florian %A Singer, Philipp %A Strohmaier, Markus %A Hotho, Andreas %D 2016 %T MixedTrails: Bayesian Hypotheses Comparison on Heterogeneous Sequential Data %U http://arxiv.org/abs/1612.07612 %X Sequential traces of user data are frequently observed online and offline, e.g.,as sequences of visited websites or as sequences of locations captured by GPS. However,understanding factors explaining the production of sequence data is a challenging task,especially since the data generation is often not homogeneous. For example, navigation behavior might change in different phases of a website visit, or movement behavior may vary between groups of user. In this work, we tackle this task and propose MixedTrails, a Bayesian approach for comparing the plausibility of hypotheses regarding the generative processes of heterogeneous sequence data. Each hypothesis represents a belief about transition probabilities between a set of states that can vary between groups of observed transitions.For example, when trying to understand human movement in a city, a hypothesis assuming tourists to be more likely to move towards points of interests than locals, can be shown to be more plausible with observed data than a hypothesis assuming the opposite. Our approach incorporates these beliefs as Bayesian priors in a generative mixed transition Markov chain model, and compares their plausibility utilizing Bayes factors. We discuss analytical and approximate inference methods for calculating the marginal likelihoods for Bayes factors,give guidance on interpreting the results, and illustrate our approach with several experiments on synthetic and empirical data from Wikipedia and Flickr. Thus, this work enables a novel kind of analysis for studying sequential data in many application areas.
• 
  What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus in ACM Transactions on the Web (2016). 10(2) 14:1--14:32.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.
  @article{doerfel2016users, abstract = {Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.}, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, journal = {ACM Transactions on the Web}, keywords = {2016 behavior bibsonomy from:nosebrain myown posts postsII project:bibsonomy selected study system tagging user}, number = 2, pages = {14:1&ndash;14:32}, title = {What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy}, volume = 10, year = 2016 }
  %0 Journal Article %1 doerfel2016users %A Doerfel, Stephan %A Zoller, Daniel %A Singer, Philipp %A Niebler, Thomas %A Hotho, Andreas %A Strohmaier, Markus %D 2016 %J ACM Transactions on the Web %N 2 %P 14:1--14:32 %T What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy %V 10 %X Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.
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  Analyzing Features for the Detection of Happy Endings in German Novels. Jannidis, Fotis; Reger, Isabella; Zehe, Albin; Becker, Martin; Hettinger, Lena; Hotho, Andreas (2016).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  With regard to a computational representation of literary plot, this paper looks at the use of sentiment analysis for happy ending detection in German novels. Its focus lies on the investigation of previously proposed sentiment features in order to gain insight about the relevance of specific features on the one hand and the implications of their performance on the other hand. Therefore, we study various partitionings of novels, considering the highly variable concept of "ending". We also show that our approach, even though still rather simple, can potentially lead to substantial findings relevant to literary studies.
  @misc{jannidis2016analyzing, abstract = {With regard to a computational representation of literary plot, this paper looks at the use of sentiment analysis for happy ending detection in German novels. Its focus lies on the investigation of previously proposed sentiment features in order to gain insight about the relevance of specific features on the one hand and the implications of their performance on the other hand. Therefore, we study various partitionings of novels, considering the highly variable concept of "ending". We also show that our approach, even though still rather simple, can potentially lead to substantial findings relevant to literary studies.}, author = {Jannidis, Fotis and Reger, Isabella and Zehe, Albin and Becker, Martin and Hettinger, Lena and Hotho, Andreas}, keywords = {dh from:albinzehe happyend kallimachos myown sentimentanalysis}, note = {cite arxiv:1611.09028}, title = {Analyzing Features for the Detection of Happy Endings in German Novels}, year = 2016 }
  %0 Generic %1 jannidis2016analyzing %A Jannidis, Fotis %A Reger, Isabella %A Zehe, Albin %A Becker, Martin %A Hettinger, Lena %A Hotho, Andreas %D 2016 %T Analyzing Features for the Detection of Happy Endings in German Novels %U http://arxiv.org/abs/1611.09028 %X With regard to a computational representation of literary plot, this paper looks at the use of sentiment analysis for happy ending detection in German novels. Its focus lies on the investigation of previously proposed sentiment features in order to gain insight about the relevance of specific features on the one hand and the implications of their performance on the other hand. Therefore, we study various partitionings of novels, considering the highly variable concept of "ending". We also show that our approach, even though still rather simple, can potentially lead to substantial findings relevant to literary studies.
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  Creation of Specific Flow-Based Training Data Sets for Usage Behaviour Classification. Otto, Florian; Ring, Markus; Landes, Dieter; Hotho, Andreas (2016). 437.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{otto2016creation, author = {Otto, Florian and Ring, Markus and Landes, Dieter and Hotho, Andreas}, booktitle = {ECCWS2016-Proceedings fo the 15th European Conference on Cyber Warfare and Security}, keywords = {behaviour classification flow myown network usage}, organization = {Academic Conferences and publishing limited}, pages = 437, title = {Creation of Specific Flow-Based Training Data Sets for Usage Behaviour Classification}, year = 2016 }
  %0 Conference Paper %1 otto2016creation %A Otto, Florian %A Ring, Markus %A Landes, Dieter %A Hotho, Andreas %B ECCWS2016-Proceedings fo the 15th European Conference on Cyber Warfare and Security %D 2016 %P 437 %T Creation of Specific Flow-Based Training Data Sets for Usage Behaviour Classification
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  Significance Testing for the Classification of Literary Subgenres. Hettinger, Lena; Jannidis, Fotis; Reger, Isabella; Hotho, Andreas (2016).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{hettinger2016significance, author = {Hettinger, Lena and Jannidis, Fotis and Reger, Isabella and Hotho, Andreas}, booktitle = {DH 2016}, keywords = {2016 classification dh digital_humanities from:schwemmlein genre kallimachos literature myown significance statistics}, title = {Significance Testing for the Classification of Literary Subgenres}, year = 2016 }
  %0 Conference Paper %1 hettinger2016significance %A Hettinger, Lena %A Jannidis, Fotis %A Reger, Isabella %A Hotho, Andreas %B DH 2016 %D 2016 %T Significance Testing for the Classification of Literary Subgenres
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  Classification of Literary Subgenres. Hettinger, Lena; Jannidis, Fotis; Reger, Isabella; Hotho, Andreas (2016).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{hettinger2016classification, author = {Hettinger, Lena and Jannidis, Fotis and Reger, Isabella and Hotho, Andreas}, booktitle = {DHd 2016}, keywords = {2016 classification dh dhd digital from:schwemmlein genre german humanities kallimachos myown novels}, title = {Classification of Literary Subgenres}, year = 2016 }
  %0 Conference Paper %1 hettinger2016classification %A Hettinger, Lena %A Jannidis, Fotis %A Reger, Isabella %A Hotho, Andreas %B DHd 2016 %D 2016 %T Classification of Literary Subgenres
• 
  Extracting Semantics from Random Walks on Wikipedia: Comparing learning and counting methods. Dallmann, Alexander; Niebler, Thomas; Lemmerich, Florian; Hotho, Andreas R. West, Zia, L., Taraborelli, D., Leskovec, J. (eds.) (2016).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Semantic relatedness between words has been extracted from a variety of sources. In this ongoing work, we explore and compare several options for determining if semantic relatedness can be extracted from navigation structures in Wikipedia. In that direction, we first investigate the potential of representation learning techniques such as DeepWalk in comparison to previously applied methods based on counting co-occurrences. Since both methods are based on (random) paths in the network, we also study different approaches to generate paths from Wikipedia link structure. For this task, we do not only consider the link structure of Wikipedia, but also actual navigation behavior of users. Finally, we analyze if semantics can also be extracted from smaller subsets of the Wikipedia link network. As a result we find that representa- tion learning techniques mostly outperform the investigated co-occurrence counting methods on the Wikipedia network. However, we find that this is not the case for paths sampled from human navigation behavior.
  @inproceedings{dallmann2016extracting, abstract = {Semantic relatedness between words has been extracted from a variety of sources. In this ongoing work, we explore and compare several options for determining if semantic relatedness can be extracted from navigation structures in Wikipedia. In that direction, we first investigate the potential of representation learning techniques such as DeepWalk in comparison to previously applied methods based on counting co-occurrences. Since both methods are based on (random) paths in the network, we also study different approaches to generate paths from Wikipedia link structure. For this task, we do not only consider the link structure of Wikipedia, but also actual navigation behavior of users. Finally, we analyze if semantics can also be extracted from smaller subsets of the Wikipedia link network. As a result we find that representa- tion learning techniques mostly outperform the investigated co-occurrence counting methods on the Wikipedia network. However, we find that this is not the case for paths sampled from human navigation behavior.}, author = {Dallmann, Alexander and Niebler, Thomas and Lemmerich, Florian and Hotho, Andreas}, booktitle = {Wiki Workshop@ICWSM}, editor = {West, Robert and Zia, Leila and Taraborelli, Dario and Leskovec, Jure}, keywords = {2016 deepwalk deepwiki from:hotho myown navigation posts postsII selected semantic wikipedia word2vec}, title = {Extracting Semantics from Random Walks on Wikipedia: Comparing learning and counting methods}, year = 2016 }
  %0 Conference Paper %1 dallmann2016extracting %A Dallmann, Alexander %A Niebler, Thomas %A Lemmerich, Florian %A Hotho, Andreas %B Wiki Workshop@ICWSM %D 2016 %E West, Robert %E Zia, Leila %E Taraborelli, Dario %E Leskovec, Jure %T Extracting Semantics from Random Walks on Wikipedia: Comparing learning and counting methods %U http://snap.stanford.edu/wikiworkshop2016/papers/wikiworkshop_icwsm2016_dallmann.pdf %X Semantic relatedness between words has been extracted from a variety of sources. In this ongoing work, we explore and compare several options for determining if semantic relatedness can be extracted from navigation structures in Wikipedia. In that direction, we first investigate the potential of representation learning techniques such as DeepWalk in comparison to previously applied methods based on counting co-occurrences. Since both methods are based on (random) paths in the network, we also study different approaches to generate paths from Wikipedia link structure. For this task, we do not only consider the link structure of Wikipedia, but also actual navigation behavior of users. Finally, we analyze if semantics can also be extracted from smaller subsets of the Wikipedia link network. As a result we find that representa- tion learning techniques mostly outperform the investigated co-occurrence counting methods on the Wikipedia network. However, we find that this is not the case for paths sampled from human navigation behavior.

2015 [ to top ]

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  Photowalking the city: comparing hypotheses about urban photo trails on Flickr. Becker, Martin; Singer, Philipp; Lemmerich, Florian; Hotho, Andreas; Helic, Denis; Strohmaier, Markus (2015).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{becker2015photowalking, address = {Beijing, China}, author = {Becker, Martin and Singer, Philipp and Lemmerich, Florian and Hotho, Andreas and Helic, Denis and Strohmaier, Markus}, booktitle = {Proceedings of the 7th International Conference on SocialInformatics (to appear)}, keywords = {behavior diss eva21 flickr folktrails from:becker hyptrails mobility myown own photo phototrails posts postsII trails urban}, month = {dec}, title = {Photowalking the city: comparing hypotheses about urban photo trails on Flickr}, type = {Publication}, year = 2015 }
  %0 Conference Paper %1 becker2015photowalking %A Becker, Martin %A Singer, Philipp %A Lemmerich, Florian %A Hotho, Andreas %A Helic, Denis %A Strohmaier, Markus %B Proceedings of the 7th International Conference on SocialInformatics (to appear) %C Beijing, China %D 2015 %T Photowalking the city: comparing hypotheses about urban photo trails on Flickr
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  Participatory Patterns in an International Air Quality Monitoring Initiative. Sîrbu, Alina; Becker, Martin; Caminiti, Saverio; De Baets, Bernard; Elen, Bart; Francis, Louise; Gravino, Pietro; Hotho, Andreas; Ingarra, Stefano; Loreto, Vittorio; Molino, Andrea; Mueller, Juergen; Peters, Jan; Ricchiuti, Ferdinando; Saracino, Fabio; Servedio, Vito D. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca; Van den Bossche, Joris (2015).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
  @misc{sirbu2015participatory, abstract = {The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.}, author = {Sîrbu, Alina and Becker, Martin and Caminiti, Saverio and De Baets, Bernard and Elen, Bart and Francis, Louise and Gravino, Pietro and Hotho, Andreas and Ingarra, Stefano and Loreto, Vittorio and Molino, Andrea and Mueller, Juergen and Peters, Jan and Ricchiuti, Ferdinando and Saracino, Fabio and Servedio, Vito D. P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca and Van den Bossche, Joris}, keywords = {2015 airprobe everyaware from:hotho myown}, note = {cite arxiv:1503.07730Comment: 17 pages, 6 figures, 1 supplementary file}, title = {Participatory Patterns in an International Air Quality Monitoring Initiative}, year = 2015 }
  %0 Generic %1 sirbu2015participatory %A Sîrbu, Alina %A Becker, Martin %A Caminiti, Saverio %A De Baets, Bernard %A Elen, Bart %A Francis, Louise %A Gravino, Pietro %A Hotho, Andreas %A Ingarra, Stefano %A Loreto, Vittorio %A Molino, Andrea %A Mueller, Juergen %A Peters, Jan %A Ricchiuti, Ferdinando %A Saracino, Fabio %A Servedio, Vito D. P. %A Stumme, Gerd %A Theunis, Jan %A Tria, Francesca %A Van den Bossche, Joris %D 2015 %T Participatory Patterns in an International Air Quality Monitoring Initiative %U http://arxiv.org/abs/1503.07730 %X The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
• 
  Genre classification on German novels. Hettinger, Lena; Becker, Martin; Reger, Isabella; Jannidis, Fotis; Hotho, Andreas (2015).
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{schwemmlein2015genre, author = {Hettinger, Lena and Becker, Martin and Reger, Isabella and Jannidis, Fotis and Hotho, Andreas}, booktitle = {Proceedings of the 12th International Workshop on Text-based Information Retrieval}, keywords = {2015 classification dh from:schwemmlein genre german kallimachos lda myown novels}, title = {Genre classification on German novels}, year = 2015 }
  %0 Conference Paper %1 schwemmlein2015genre %A Hettinger, Lena %A Becker, Martin %A Reger, Isabella %A Jannidis, Fotis %A Hotho, Andreas %B Proceedings of the 12th International Workshop on Text-based Information Retrieval %D 2015 %T Genre classification on German novels %U http://www.uni-weimar.de/medien/webis/events/tir-15/tir15-papers-final/Hettinger2015-tir-paper.pdf
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  Participatory Patterns in an International Air Quality Monitoring Initiative. Sîrbu, Alina; Becker, Martin; Caminiti, Saverio; De Baets, Bernard; Elen, Bart; Francis, Louise; Gravino, Pietro; Hotho, Andreas; Ingarra, Stefano; Loreto, Vittorio; Molino, Andrea; Mueller, Juergen; Peters, Jan; Ricchiuti, Ferdinando; Saracino, Fabio; Servedio, Vito D. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca; Van den Bossche, Joris in PLoS ONE (2015). 10(8) e0136763.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  <p>The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.</p>
  @article{10.1371/journal.pone.0136763, abstract = {<p>The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.</p>}, author = {Sîrbu, Alina and Becker, Martin and Caminiti, Saverio and De Baets, Bernard and Elen, Bart and Francis, Louise and Gravino, Pietro and Hotho, Andreas and Ingarra, Stefano and Loreto, Vittorio and Molino, Andrea and Mueller, Juergen and Peters, Jan and Ricchiuti, Ferdinando and Saracino, Fabio and Servedio, Vito D. P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca and Van den Bossche, Joris}, journal = {PLoS ONE}, keywords = {air airprobe environmental environmental:selected everyaware from:hotho game myown pollution quality}, month = {08}, number = 8, pages = {e0136763}, publisher = {Public Library of Science}, title = {Participatory Patterns in an International Air Quality Monitoring Initiative}, volume = 10, year = 2015 }
  %0 Journal Article %1 10.1371/journal.pone.0136763 %A Sîrbu, Alina %A Becker, Martin %A Caminiti, Saverio %A De Baets, Bernard %A Elen, Bart %A Francis, Louise %A Gravino, Pietro %A Hotho, Andreas %A Ingarra, Stefano %A Loreto, Vittorio %A Molino, Andrea %A Mueller, Juergen %A Peters, Jan %A Ricchiuti, Ferdinando %A Saracino, Fabio %A Servedio, Vito D. P. %A Stumme, Gerd %A Theunis, Jan %A Tria, Francesca %A Van den Bossche, Joris %D 2015 %I Public Library of Science %J PLoS ONE %N 8 %P e0136763 %R 10.1371/journal.pone.0136763 %T Participatory Patterns in an International Air Quality Monitoring Initiative %U http://dx.doi.org/10.1371%2Fjournal.pone.0136763 %V 10 %X <p>The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.</p>
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  VizTrails: An Information Visualization Tool for Exploring Geographic Movement Trajectories. Becker, Martin; Singer, Philipp; Lemmerich, Florian; Hotho, Andreas; Helic, Denis; Strohmaier, Markus in HT '15 (2015). 319--320.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Understanding the way people move through urban areas represents an important problem that has implications for a range of societal challenges such as city planning, public transportation, or crime analysis. In this paper, we present an interactive visualization tool called VizTrails for exploring and understanding such human movement. It features visualizations that show aggregated statistics of trails for geographic areas that correspond to grid cells on a map, e.g., on the number of users passing through or on cells commonly visited next. Amongst other features, system allows to overlay the map with the results of SPARQL queries in order to relate the observed trajectory statistics with its geo-spatial context, e.g., considering a city's points of interest. The systems functionality is demonstrated using trajectory examples extracted from the social photo sharing platform Flickr. Overall, VizTrails facilitates deeper insights into geo-spatial trajectory data by enabling interactive exploration of aggregated statistics and providing geo-spatial context.
  @inproceedings{Becker:2015:VIV:2700171.2791021, abstract = {Understanding the way people move through urban areas represents an important problem that has implications for a range of societal challenges such as city planning, public transportation, or crime analysis. In this paper, we present an interactive visualization tool called VizTrails for exploring and understanding such human movement. It features visualizations that show aggregated statistics of trails for geographic areas that correspond to grid cells on a map, e.g., on the number of users passing through or on cells commonly visited next. Amongst other features, system allows to overlay the map with the results of SPARQL queries in order to relate the observed trajectory statistics with its geo-spatial context, e.g., considering a city's points of interest. The systems functionality is demonstrated using trajectory examples extracted from the social photo sharing platform Flickr. Overall, VizTrails facilitates deeper insights into geo-spatial trajectory data by enabling interactive exploration of aggregated statistics and providing geo-spatial context.}, address = {New York, NY, USA}, author = {Becker, Martin and Singer, Philipp and Lemmerich, Florian and Hotho, Andreas and Helic, Denis and Strohmaier, Markus}, booktitle = {Proceedings of the 26th ACM Conference on Hypertext \&\#38; Social Media}, keywords = {2016 from:hotho gis hyptrails myown posts postsII viztails}, pages = {319&ndash;320}, publisher = {ACM}, series = {HT '15}, title = {VizTrails: An Information Visualization Tool for Exploring Geographic Movement Trajectories}, year = 2015 }
  %0 Conference Paper %1 Becker:2015:VIV:2700171.2791021 %A Becker, Martin %A Singer, Philipp %A Lemmerich, Florian %A Hotho, Andreas %A Helic, Denis %A Strohmaier, Markus %B Proceedings of the 26th ACM Conference on Hypertext &#38; Social Media %C New York, NY, USA %D 2015 %I ACM %P 319--320 %R 10.1145/2700171.2791021 %T VizTrails: An Information Visualization Tool for Exploring Geographic Movement Trajectories %U http://doi.acm.org/10.1145/2700171.2791021 %X Understanding the way people move through urban areas represents an important problem that has implications for a range of societal challenges such as city planning, public transportation, or crime analysis. In this paper, we present an interactive visualization tool called VizTrails for exploring and understanding such human movement. It features visualizations that show aggregated statistics of trails for geographic areas that correspond to grid cells on a map, e.g., on the number of users passing through or on cells commonly visited next. Amongst other features, system allows to overlay the map with the results of SPARQL queries in order to relate the observed trajectory statistics with its geo-spatial context, e.g., considering a city's points of interest. The systems functionality is demonstrated using trajectory examples extracted from the social photo sharing platform Flickr. Overall, VizTrails facilitates deeper insights into geo-spatial trajectory data by enabling interactive exploration of aggregated statistics and providing geo-spatial context. %@ 978-1-4503-3395-5
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  ConDist: A Context-Driven Categorical Distance Measure. Ring, Markus; Otto, Florian; Becker, Martin; Niebler, Thomas; Landes, Dieter; Hotho, Andreas ECMLPKDD2015 (ed.) (2015).
  [ BibTeX ] [ EndNote ]
   
  @inproceedings{ring2015condist, author = {Ring, Markus and Otto, Florian and Becker, Martin and Niebler, Thomas and Landes, Dieter and Hotho, Andreas}, editor = {ECMLPKDD2015}, keywords = {2015 categorical data from:hotho learning measure myown similarity unsupervised}, title = {ConDist: A Context-Driven Categorical Distance Measure}, year = 2015 }
  %0 Conference Paper %1 ring2015condist %A Ring, Markus %A Otto, Florian %A Becker, Martin %A Niebler, Thomas %A Landes, Dieter %A Hotho, Andreas %D 2015 %E ECMLPKDD2015, %T ConDist: A Context-Driven Categorical Distance Measure
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  Exploratory subgroup analytics on ubiquitous data. Atzmueller, Martin; Mueller, Juergen; Becker, Martin in Mining, Modeling and Recommending 'Things' in Social Media (2015). (Vol. 8940) 1--20.
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @incollection{atzmueller2015exploratory, author = {Atzmueller, Martin and Mueller, Juergen and Becker, Martin}, booktitle = {Mining, Modeling and Recommending 'Things' in Social Media}, keywords = {analytics eva21 mining myown proposal subgroup ubiquitious from:becker}, pages = {1&ndash;20}, series = {Lecture Notes in Computer Science}, title = {Exploratory subgroup analytics on ubiquitous data}, volume = 8940, year = 2015 }
  %0 Book Section %1 atzmueller2015exploratory %A Atzmueller, Martin %A Mueller, Juergen %A Becker, Martin %B Mining, Modeling and Recommending 'Things' in Social Media %D 2015 %P 1--20 %T Exploratory subgroup analytics on ubiquitous data %V 8940
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  Automatic Threshold Calculation for the Categorical Distance Measure ConDist. Ring, Markus; Landes, Dieter; Hotho, Andreas in CEUR Workshop Proceedings, R. Bergmann, Görg, S., Müller, G. (eds.) (2015). (Vol. 1458) 52-63.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{ring2015automatic, author = {Ring, Markus and Landes, Dieter and Hotho, Andreas}, booktitle = {LWA}, crossref = {conf/lwa/2015}, editor = {Bergmann, Ralph and Görg, Sebastian and Müller, Gilbert}, keywords = {myown from:markus0412}, pages = {52-63}, publisher = {CEUR-WS.org}, series = {CEUR Workshop Proceedings}, title = {Automatic Threshold Calculation for the Categorical Distance Measure ConDist.}, volume = 1458, year = 2015 }
  %0 Conference Paper %1 ring2015automatic %A Ring, Markus %A Landes, Dieter %A Hotho, Andreas %B LWA %D 2015 %E Bergmann, Ralph %E Görg, Sebastian %E Müller, Gilbert %I CEUR-WS.org %P 52-63 %T Automatic Threshold Calculation for the Categorical Distance Measure ConDist. %U http://dblp.uni-trier.de/db/conf/lwa/lwa2015.html#RingLH15 %V 1458
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  Evaluating Emergent Semantics in Folksonomies on Human Intuition Niebler, Thomas; Becker, Martin; Zoller, Daniel; Doerfel, Stephan; Hotho, Andreas (2015).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @techreport{tr_niebler2015evaluating, author = {Niebler, Thomas and Becker, Martin and Zoller, Daniel and Doerfel, Stephan and Hotho, Andreas}, keywords = {evaluation from:thoni human intuition myown semantic semantics wordnet}, title = {Evaluating Emergent Semantics in Folksonomies on Human Intuition}, year = 2015 }
  %0 Report %1 tr_niebler2015evaluating %A Niebler, Thomas %A Becker, Martin %A Zoller, Daniel %A Doerfel, Stephan %A Hotho, Andreas %D 2015 %T Evaluating Emergent Semantics in Folksonomies on Human Intuition
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  Hyptrails: A bayesian approach for comparing hypotheses about human trails. Singer, P.; Helic, D.; Hotho, A.; Strohmaier, M. (2015).
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{singer2015hyptrails, address = {Firenze, Italy}, author = {Singer, P. and Helic, D. and Hotho, A. and Strohmaier, M.}, booktitle = {24th International World Wide Web Conference (WWW2015)}, keywords = {2015 bibsonomy compare from:hotho human hypotheses hyptrails myown trails web}, month = {May 18 - May 22}, organization = {ACM}, publisher = {ACM}, title = {Hyptrails: A bayesian approach for comparing hypotheses about human trails}, year = 2015 }
  %0 Conference Paper %1 singer2015hyptrails %A Singer, P. %A Helic, D. %A Hotho, A. %A Strohmaier, M. %B 24th International World Wide Web Conference (WWW2015) %C Firenze, Italy %D 2015 %I ACM %T Hyptrails: A bayesian approach for comparing hypotheses about human trails %U http://www.www2015.it/documents/proceedings/proceedings/p1003.pdf
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  Participatory patterns in an international air quality monitoring initiative. Sirbu, Alina; Becker, Martin; Caminiti, Saverio; De Baets, Bernard; Elen, Bart; Francis, Louise; Gravino, Pietro; Hotho, Andreas; Ingarra, Stefano; Loreto, Vittorio; Molino, Andrea; Mueller, Juergen; Peters, Jan; Ricchiuti, Ferdinando; Saracino, Fabio; Servedio, Vito D. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca; Van den Bossche, Joris in PLoS ONE (2015). 10(8) e0136763.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
  @article{sirbu2015participatory, abstract = {The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.}, author = {Sirbu, Alina and Becker, Martin and Caminiti, Saverio and De Baets, Bernard and Elen, Bart and Francis, Louise and Gravino, Pietro and Hotho, Andreas and Ingarra, Stefano and Loreto, Vittorio and Molino, Andrea and Mueller, Juergen and Peters, Jan and Ricchiuti, Ferdinando and Saracino, Fabio and Servedio, Vito D. P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca and Van den Bossche, Joris}, journal = {PLoS ONE}, keywords = {air airprobe behaviour behavioural change cv diss diss:allmypubs eva21 from:becker inthesis myown own pollution quality selected}, month = {08}, number = 8, pages = {e0136763}, publisher = {Public Library of Science}, title = {Participatory patterns in an international air quality monitoring initiative}, volume = 10, year = 2015 }
  %0 Journal Article %1 sirbu2015participatory %A Sirbu, Alina %A Becker, Martin %A Caminiti, Saverio %A De Baets, Bernard %A Elen, Bart %A Francis, Louise %A Gravino, Pietro %A Hotho, Andreas %A Ingarra, Stefano %A Loreto, Vittorio %A Molino, Andrea %A Mueller, Juergen %A Peters, Jan %A Ricchiuti, Ferdinando %A Saracino, Fabio %A Servedio, Vito D. P. %A Stumme, Gerd %A Theunis, Jan %A Tria, Francesca %A Van den Bossche, Joris %D 2015 %I Public Library of Science %J PLoS ONE %N 8 %P e0136763 %T Participatory patterns in an international air quality monitoring initiative %U http://dx.doi.org/10.1371%2Fjournal.pone.0136763 %V 10 %X The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
• 
  Media Bias in German Online Newspapers. Dallmann, Alexander; Lemmerich, Florian; Zoller, Daniel; Hotho, Andreas (2015).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{dallmann2015media, address = {Cyprus, Turkey, September 1-4}, author = {Dallmann, Alexander and Lemmerich, Florian and Zoller, Daniel and Hotho, Andreas}, booktitle = {26th ACM Conference on Hypertext and Social Media}, keywords = {2015 bias german media myown news newspaper from:hotho}, publisher = {ACM}, title = {Media Bias in German Online Newspapers}, year = 2015 }
  %0 Conference Paper %1 dallmann2015media %A Dallmann, Alexander %A Lemmerich, Florian %A Zoller, Daniel %A Hotho, Andreas %B 26th ACM Conference on Hypertext and Social Media %C Cyprus, Turkey, September 1-4 %D 2015 %I ACM %T Media Bias in German Online Newspapers
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  Modeling and Extracting Load Intensity Profiles. v. Kistowski, Jóakim; Nikolas, Herbst.; Zoller, Daniel; Kounev, Samuel; Hotho, Andreas (2015).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.
  @inproceedings{vkistowski2015toappearmodeling, abstract = {Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.}, author = {v. Kistowski, Jóakim and Nikolas, Herbst. and Zoller, Daniel and Kounev, Samuel and Hotho, Andreas}, booktitle = {Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)}, keywords = {extracting from:nosebrain intensity load modeling myown profile project:bibsonomy}, title = {Modeling and Extracting Load Intensity Profiles}, year = 2015 }
  %0 Conference Paper %1 vkistowski2015toappearmodeling %A v. Kistowski, Jóakim %A Nikolas, Herbst. %A Zoller, Daniel %A Kounev, Samuel %A Hotho, Andreas %B Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) %D 2015 %T Modeling and Extracting Load Intensity Profiles %X Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.
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  On Publication Usage in a Social Bookmarking System. Zoller, Daniel; Doerfel, Stephan; Jäschke, Robert; Stumme, Gerd; Hotho, Andreas (2015).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.
  @inproceedings{zoller2015publication, abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.}, author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas}, booktitle = {Proceedings of the 2015 ACM Conference on Web Science}, keywords = {altmetrics bookmarking impact myown publication short:zoller2015publusage social usage from:nosebrain}, title = {On Publication Usage in a Social Bookmarking System}, year = 2015 }
  %0 Conference Paper %1 zoller2015publication %A Zoller, Daniel %A Doerfel, Stephan %A Jäschke, Robert %A Stumme, Gerd %A Hotho, Andreas %B Proceedings of the 2015 ACM Conference on Web Science %D 2015 %T On Publication Usage in a Social Bookmarking System %X Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.
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  MicroTrails: Comparing Hypotheses About Task Selection on a Crowdsourcing Platform. Becker, Martin; Borchert, Kathrin; Hirth, Matthias; Mewes, Hauke; Hotho, Andreas; Tran-Gia, Phuoc in i-KNOW '15 (2015). 10:1--10:8.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{becker2015microtrails, address = {New York, NY, USA}, author = {Becker, Martin and Borchert, Kathrin and Hirth, Matthias and Mewes, Hauke and Hotho, Andreas and Tran-Gia, Phuoc}, booktitle = {Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business}, keywords = {crowdsourcing eva21 from:becker hyptrails incentives microtrails myown navigation own posts postsII}, month = {oct}, pages = {10:1&ndash;10:8}, publisher = {ACM}, series = {i-KNOW '15}, title = {MicroTrails: Comparing Hypotheses About Task Selection on a Crowdsourcing Platform}, year = 2015 }
  %0 Conference Paper %1 becker2015microtrails %A Becker, Martin %A Borchert, Kathrin %A Hirth, Matthias %A Mewes, Hauke %A Hotho, Andreas %A Tran-Gia, Phuoc %B Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business %C New York, NY, USA %D 2015 %I ACM %P 10:1--10:8 %T MicroTrails: Comparing Hypotheses About Task Selection on a Crowdsourcing Platform %U http://doi.acm.org/10.1145/2809563.2809608

2014 [ to top ]

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  Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014 Cellier, Peggy; Charnois, Thierry; Hotho, Andreas; Matwin, Stan; Moens, Marie-Francine; Toussaint, Yannick in CEUR Workshop Proceedings (2014). (Vol. 1202) CEUR-WS.org.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @proceedings{cellier2014proceedings, editor = {Cellier, Peggy and Charnois, Thierry and Hotho, Andreas and Matwin, Stan and Moens, Marie{-}Francine and Toussaint, Yannick}, keywords = {2014 data from:hotho mining myown nlp workshop}, publisher = {CEUR-WS.org}, series = {{CEUR} Workshop Proceedings}, title = {Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014}, volume = 1202, year = 2014 }
  %0 Conference Proceedings %1 cellier2014proceedings %B CEUR Workshop Proceedings %D 2014 %E Cellier, Peggy %E Charnois, Thierry %E Hotho, Andreas %E Matwin, Stan %E Moens, Marie-Francine %E Toussaint, Yannick %I CEUR-WS.org %T Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014 %U http://ceur-ws.org/Vol-1202 %V 1202
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  HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web. Singer, Philipp; Helic, Denis; Hotho, Andreas; Strohmaier, Markus (2014).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web.
  @misc{singer2014hyptrails, abstract = {When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web.}, author = {Singer, Philipp and Helic, Denis and Hotho, Andreas and Strohmaier, Markus}, keywords = {2014 bayesian comparing from:hotho hypotheses myown social}, title = {HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web}, year = 2014 }
  %0 Generic %1 singer2014hyptrails %A Singer, Philipp %A Helic, Denis %A Hotho, Andreas %A Strohmaier, Markus %D 2014 %T HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web %X When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web.
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  Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014 Jannach, Dietmar; Freyne, Jill; Geyer, Werner; Guy, Ido; Hotho, Andreas; Mobasher, Bamshad in CEUR Workshop Proceedings (2014). (Vol. 1271) CEUR-WS.org.
  [ BibTeX ] [ EndNote ] [ URL ]
   
  @proceedings{jannach2014proceedings, editor = {Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad}, keywords = {2014 from:hotho myown proceedings recommender social workshop}, publisher = {CEUR-WS.org}, series = {{CEUR} Workshop Proceedings}, title = {Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th {ACM} Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014}, volume = 1271, year = 2014 }
  %0 Conference Proceedings %1 jannach2014proceedings %B CEUR Workshop Proceedings %D 2014 %E Jannach, Dietmar %E Freyne, Jill %E Geyer, Werner %E Guy, Ido %E Hotho, Andreas %E Mobasher, Bamshad %I CEUR-WS.org %T Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014 %U http://ceur-ws.org/Vol-1271 %V 1271
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  Of course we share! Testing Assumptions about Social Tagging Systems. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus (2014).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.
  @misc{doerfel2014course, abstract = {Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.}, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, keywords = {2014 from:hotho myown posts postsII share social tagging}, note = {cite arxiv:1401.0629}, title = {Of course we share! Testing Assumptions about Social Tagging Systems}, year = 2014 }
  %0 Generic %1 doerfel2014course %A Doerfel, Stephan %A Zoller, Daniel %A Singer, Philipp %A Niebler, Thomas %A Hotho, Andreas %A Strohmaier, Markus %D 2014 %T Of course we share! Testing Assumptions about Social Tagging Systems %U http://arxiv.org/abs/1401.0629 %X Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.
• 
  The sixth ACM RecSys workshop on recommender systems and the social web. Jannach, Dietmar; Freyne, Jill; Geyer, Werner; Guy, Ido; Hotho, Andreas; Mobasher, Bamshad (2014). 395.
  [ BibTeX ] [ EndNote ] [ URL ]
   
  @inproceedings{jannach2014sixth, author = {Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad}, booktitle = {Eighth {ACM} Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, {USA} - October 06 - 10, 2014}, keywords = {2014 from:hotho introduction myown recommender social workshop}, pages = 395, title = {The sixth {ACM} RecSys workshop on recommender systems and the social web}, year = 2014 }
  %0 Conference Paper %1 jannach2014sixth %A Jannach, Dietmar %A Freyne, Jill %A Geyer, Werner %A Guy, Ido %A Hotho, Andreas %A Mobasher, Bamshad %B Eighth ACM Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, USA - October 06 - 10, 2014 %D 2014 %P 395 %R 10.1145/2645710.2645786 %T The sixth ACM RecSys workshop on recommender systems and the social web %U http://doi.acm.org/10.1145/2645710.2645786
• 
  How Social is Social Tagging? Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus in WWW 2014 (2014).
  [ BibTeX ] [ EndNote ] [ Download ]
   
  @inproceedings{doerfel2014social, address = {New York, NY, USA}, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, booktitle = {Proceedings of the 23rd International World Wide Web Conference}, keywords = {2014 WWW analyis behavior from:hotho log myown posts postsii social tagging}, publisher = {ACM}, series = {WWW 2014}, title = {How Social is Social Tagging?}, year = 2014 }
  %0 Conference Paper %1 doerfel2014social %A Doerfel, Stephan %A Zoller, Daniel %A Singer, Philipp %A Niebler, Thomas %A Hotho, Andreas %A Strohmaier, Markus %B Proceedings of the 23rd International World Wide Web Conference %C New York, NY, USA %D 2014 %I ACM %T How Social is Social Tagging?
• 
  Ubicon and its Applications for Ubiquitous Social Computing. Atzmueller, Martin; Becker, Martin; Kibanov, Mark; Scholz, Christoph; Doerfel, Stephan; Hotho, Andreas; Macek, Bjoern-Elmar; Mitzlaff, Folke; Mueller, Juergen; Stumme, Gerd in New Review of Hypermedia and Multimedia (2014). 20(1) 53--77.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques and tools. In this paper, we focus on the Ubicon platform, its applications, and a large spectrum of analysis results. Ubicon provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of Ubicon. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing Ubicon.
  @article{atzmueller2014ubicon, abstract = {The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques and tools. In this paper, we focus on the Ubicon platform, its applications, and a large spectrum of analysis results. Ubicon provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of Ubicon. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing Ubicon.}, author = {Atzmueller, Martin and Becker, Martin and Kibanov, Mark and Scholz, Christoph and Doerfel, Stephan and Hotho, Andreas and Macek, Bjoern-Elmar and Mitzlaff, Folke and Mueller, Juergen and Stumme, Gerd}, journal = {New Review of Hypermedia and Multimedia}, keywords = {2014 analytics from:hotho mining myown social ubicon ubiquitous}, number = 1, pages = {53&ndash;77}, title = {{Ubicon and its Applications for Ubiquitous Social Computing}}, volume = 20, year = 2014 }
  %0 Journal Article %1 atzmueller2014ubicon %A Atzmueller, Martin %A Becker, Martin %A Kibanov, Mark %A Scholz, Christoph %A Doerfel, Stephan %A Hotho, Andreas %A Macek, Bjoern-Elmar %A Mitzlaff, Folke %A Mueller, Juergen %A Stumme, Gerd %D 2014 %J New Review of Hypermedia and Multimedia %N 1 %P 53--77 %R 10.1080/13614568.2013.873488 %T Ubicon and its Applications for Ubiquitous Social Computing %U http://www.tandfonline.com/doi/abs/10.1080/13614568.2013.873488 %V 20 %X The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques and tools. In this paper, we focus on the Ubicon platform, its applications, and a large spectrum of analysis results. Ubicon provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of Ubicon. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing Ubicon.
• 
  Folksonomies. Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus in Encyclopedia of Social Network Analysis and Mining (2014). 542--547.
  [ BibTeX ] [ EndNote ]
   
  @incollection{singer2014folksonomies, author = {Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, booktitle = {Encyclopedia of Social Network Analysis and Mining}, keywords = {2014 characterization folksonomy from:hotho myown posts postsi semantic}, pages = {542&ndash;547}, publisher = {Springer}, title = {Folksonomies}, year = 2014 }
  %0 Book Section %1 singer2014folksonomies %A Singer, Philipp %A Niebler, Thomas %A Hotho, Andreas %A Strohmaier, Markus %B Encyclopedia of Social Network Analysis and Mining %D 2014 %I Springer %P 542--547 %T Folksonomies
• 
  Evaluating Assumptions about Social Tagging - A Study of User Behavior in BibSonomy. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus in CEUR Workshop Proceedings, T. Seidl, Hassani, M., Beecks, C. (eds.) (2014). (Vol. 1226) 18--19.
  [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  @inproceedings{doerfel2014evaluating, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, booktitle = {Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014.}, crossref = {DBLP:conf/lwa/2014}, editor = {Seidl, Thomas and Hassani, Marwan and Beecks, Christian}, keywords = {assumption behavior bibsonomy from:nosebrain law myown project:bibsonomy social tagging user}, pages = {18&ndash;19}, publisher = {CEUR-WS.org}, series = {{CEUR} Workshop Proceedings}, title = {Evaluating Assumptions about Social Tagging - {A} Study of User Behavior in BibSonomy}, volume = 1226, year = 2014 }
  %0 Conference Paper %1 doerfel2014evaluating %A Doerfel, Stephan %A Zoller, Daniel %A Singer, Philipp %A Niebler, Thomas %A Hotho, Andreas %A Strohmaier, Markus %B Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. %D 2014 %E Seidl, Thomas %E Hassani, Marwan %E Beecks, Christian %I CEUR-WS.org %P 18--19 %T Evaluating Assumptions about Social Tagging - A Study of User Behavior in BibSonomy %U http://ceur-ws.org/Vol-1226/paper06.pdf %V 1226
• 
  Finding Enclosures for Linear Systems Using Interval Matrix Multiplication in CUDA. Dallmann, Alexander; Beck, Philip-Daniel; von Gudenberg, JürgenWolff in Parallel Processing and Applied Mathematics, R. Wyrzykowski, Dongarra, J., Karczewski, K., Waśniewski, J. (eds.) (2014). (Vol. 8385) 582-590.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  In this paper we present CUDA kernels that compute an interval matrix product. Starting from a naive implementation we investigate possible speedups using commonly known techniques from standard matrix multiplication. We also evaluate the achieved speedup when our kernels are used to accelerate a variant of an existing algorithm that finds an enclosure for the solution of a linear system. Moreover the quality of our enclosure is discussed.
  @incollection{noKey, abstract = {In this paper we present CUDA kernels that compute an interval matrix product. Starting from a naive implementation we investigate possible speedups using commonly known techniques from standard matrix multiplication. We also evaluate the achieved speedup when our kernels are used to accelerate a variant of an existing algorithm that finds an enclosure for the solution of a linear system. Moreover the quality of our enclosure is discussed.}, author = {Dallmann, Alexander and Beck, Philip-Daniel and von Gudenberg, JürgenWolff}, booktitle = {Parallel Processing and Applied Mathematics}, editor = {Wyrzykowski, Roman and Dongarra, Jack and Karczewski, Konrad and Waśniewski, Jerzy}, keywords = {cuda enclosures linear_systems myown from:dallmann}, pages = {582-590}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, title = {Finding Enclosures for Linear Systems Using Interval Matrix Multiplication in CUDA}, volume = 8385, year = 2014 }
  %0 Book Section %1 noKey %A Dallmann, Alexander %A Beck, Philip-Daniel %A von Gudenberg, JürgenWolff %B Parallel Processing and Applied Mathematics %D 2014 %E Wyrzykowski, Roman %E Dongarra, Jack %E Karczewski, Konrad %E Waśniewski, Jerzy %I Springer Berlin Heidelberg %P 582-590 %R 10.1007/978-3-642-55195-6_55 %T Finding Enclosures for Linear Systems Using Interval Matrix Multiplication in CUDA %U http://dx.doi.org/10.1007/978-3-642-55195-6_55 %V 8385 %X In this paper we present CUDA kernels that compute an interval matrix product. Starting from a naive implementation we investigate possible speedups using commonly known techniques from standard matrix multiplication. We also evaluate the achieved speedup when our kernels are used to accelerate a variant of an existing algorithm that finds an enclosure for the solution of a linear system. Moreover the quality of our enclosure is discussed. %@ 978-3-642-55194-9
• 
  The social distributional hypothesis: a pragmatic proxy for homophily in online social networks. Mitzlaff, Folke; Atzmueller, Martin; Hotho, Andreas; Stumme, Gerd in Social Network Analysis and Mining (2014). 4(1)
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the
  @article{noKey, abstract = {Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the}, author = {Mitzlaff, Folke and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd}, journal = {Social Network Analysis and Mining}, keywords = {2014 distributional from:hotho hypothesis myown pragmatic proxy social}, number = 1, publisher = {Springer Vienna}, title = {The social distributional hypothesis: a pragmatic proxy for homophily in online social networks}, volume = 4, year = 2014 }
  %0 Journal Article %1 noKey %A Mitzlaff, Folke %A Atzmueller, Martin %A Hotho, Andreas %A Stumme, Gerd %D 2014 %I Springer Vienna %J Social Network Analysis and Mining %N 1 %R 10.1007/s13278-014-0216-2 %T The social distributional hypothesis: a pragmatic proxy for homophily in online social networks %U http://dx.doi.org/10.1007/s13278-014-0216-2 %V 4 %X Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the
• 
  Subjective vs. Objective Data: Bridging the Gap. Becker, Martin; Hotho, Andreas; Mueller, Juergen; Kibanov, Mark; Atzmueller, Martin; Stumme, Gerd (2014).
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ]
   
  Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions.
  @misc{becker2014subjective, abstract = {Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions.}, author = {Becker, Martin and Hotho, Andreas and Mueller, Juergen and Kibanov, Mark and Atzmueller, Martin and Stumme, Gerd}, howpublished = {CSSWS 2014, Poster}, keywords = {2015 everyaware from:hotho myown}, title = {Subjective vs. Objective Data: Bridging the Gap}, year = 2014 }
  %0 Generic %1 becker2014subjective %A Becker, Martin %A Hotho, Andreas %A Mueller, Juergen %A Kibanov, Mark %A Atzmueller, Martin %A Stumme, Gerd %D 2014 %T Subjective vs. Objective Data: Bridging the Gap %U http://www.gesis.org/en/events/css-wintersymposium/poster-presentation/ %X Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions.

2013 [ to top ]

• 
  Computing semantic relatedness from human navigational paths on Wikipedia. Singer, Philipp; Niebler, Thomas; Strohmaier, Markus; Hotho, Andreas in WWW '13 Companion, ACM (ed.) (2013). 171--172.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  This paper presents a novel approach for computing semantic relatedness between concepts on Wikipedia by using human navigational paths for this task. Our results suggest that human navigational paths provide a viable source for calculating semantic relatedness between concepts on Wikipedia. We also show that we can improve accuracy by intelligent selection of path corpora based on path characteristics indicating that not all paths are equally useful. Our work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.
  @inproceedings{singer2013computing, abstract = {This paper presents a novel approach for computing semantic relatedness between concepts on Wikipedia by using human navigational paths for this task. Our results suggest that human navigational paths provide a viable source for calculating semantic relatedness between concepts on Wikipedia. We also show that we can improve accuracy by intelligent selection of path corpora based on path characteristics indicating that not all paths are equally useful. Our work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.}, address = {Republic and Canton of Geneva, Switzerland}, author = {Singer, Philipp and Niebler, Thomas and Strohmaier, Markus and Hotho, Andreas}, booktitle = {Proceedings of the 22nd international conference on World Wide Web companion}, editor = {ACM}, keywords = {from:thoni human myown navigational paths posts postsi relatedness selected semantic wikipedia}, pages = {171&ndash;172}, publisher = {International World Wide Web Conferences Steering Committee}, series = {WWW '13 Companion}, title = {Computing semantic relatedness from human navigational paths on Wikipedia}, year = 2013 }
  %0 Conference Paper %1 singer2013computing %A Singer, Philipp %A Niebler, Thomas %A Strohmaier, Markus %A Hotho, Andreas %B Proceedings of the 22nd international conference on World Wide Web companion %C Republic and Canton of Geneva, Switzerland %D 2013 %E ACM, %I International World Wide Web Conferences Steering Committee %P 171--172 %T Computing semantic relatedness from human navigational paths on Wikipedia %U http://dl.acm.org/citation.cfm?id=2487788.2487873 %X This paper presents a novel approach for computing semantic relatedness between concepts on Wikipedia by using human navigational paths for this task. Our results suggest that human navigational paths provide a viable source for calculating semantic relatedness between concepts on Wikipedia. We also show that we can improve accuracy by intelligent selection of path corpora based on path characteristics indicating that not all paths are equally useful. Our work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task. %@ 978-1-4503-2038-2
• 
  Semantics of User Interaction in Social Media. Mitzlaff, Folke; Atzmueller, Martin; Stumme, Gerd; Hotho, Andreas in Complex Networks IV, G. Ghoshal, Poncela-Casasnovas, J., Tolksdorf, R. (eds.) (2013). (Vol. 476)
  [ BibTeX ] [ EndNote ]
   
  @incollection{MASH:13, address = {Heidelberg, Germany}, author = {Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas}, booktitle = {Complex Networks IV}, editor = {Ghoshal, Gourab and Poncela-Casasnovas, Julia and Tolksdorf, Robert}, keywords = {2013 from:hotho media myown semantic social user}, publisher = {Springer Verlag}, series = {Studies in Computational Intelligence}, title = {{Semantics of User Interaction in Social Media}}, volume = 476, year = 2013 }
  %0 Book Section %1 MASH:13 %A Mitzlaff, Folke %A Atzmueller, Martin %A Stumme, Gerd %A Hotho, Andreas %B Complex Networks IV %C Heidelberg, Germany %D 2013 %E Ghoshal, Gourab %E Poncela-Casasnovas, Julia %E Tolksdorf, Robert %I Springer Verlag %R 10.1007/978-3-642-36844-8_2 %T Semantics of User Interaction in Social Media %V 476
• 
  Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers Atzmueller, Martin; Chin, Alvin; Helic, Denis; Hotho, Andreas (2013). Imprint: Springer, Berlin, Heidelberg.
  [ BibTeX ] [ EndNote ] [ URL ]
   
  @book{atzmueller2013ubiquitous, address = {Berlin, Heidelberg}, editor = {Atzmueller, Martin and Chin, Alvin and Helic, Denis and Hotho, Andreas}, keywords = {2013 analysis bibsonomy from:hotho media myown postproceedings social workshop}, publisher = {Imprint: Springer}, title = {Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers}, year = 2013 }
  %0 Book %1 atzmueller2013ubiquitous %C Berlin, Heidelberg %D 2013 %E Atzmueller, Martin %E Chin, Alvin %E Helic, Denis %E Hotho, Andreas %I Imprint: Springer %T Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers %U http://link.springer.com/book/10.1007/978-3-642-45392-2 %@ 9783642453915 3642453910 9783642453922 3642453929
• 
  Exploiting Structural Consistencies with Stacked Conditional Random Fields. Kluegl, Peter; Toepfer, Martin; Lemmerich, Florian; Hotho, Andreas; Puppe, Frank in Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics (2013). 30 111-125.
  [ Abstract ] [ BibTeX ] [ EndNote ]
   
  Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches, these undirected graphical models assume the instances to be independently distributed. However, in real-world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. We apply rule learning collectively on the predictions of an initial CRF for one context to acquire descriptions of its specific properties. Then, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.
  @article{kluegl2013exploiting, abstract = {Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches, these undirected graphical models assume the instances to be independently distributed. However, in real-world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. We apply rule learning collectively on the predictions of an initial CRF for one context to acquire descriptions of its specific properties. Then, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.}, author = {Kluegl, Peter and Toepfer, Martin and Lemmerich, Florian and Hotho, Andreas and Puppe, Frank}, journal = {Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics}, keywords = {2013 from:hotho ie learning myown references}, pages = {111-125}, title = {Exploiting Structural Consistencies with Stacked Conditional Random Fields}, volume = 30, year = 2013 }
  %0 Journal Article %1 kluegl2013exploiting %A Kluegl, Peter %A Toepfer, Martin %A Lemmerich, Florian %A Hotho, Andreas %A Puppe, Frank %D 2013 %J Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics %P 111-125 %T Exploiting Structural Consistencies with Stacked Conditional Random Fields %V 30 %X Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches, these undirected graphical models assume the instances to be independently distributed. However, in real-world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. We apply rule learning collectively on the predictions of an initial CRF for one context to acquire descriptions of its specific properties. Then, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.
• 
  A Generic Platform for Ubiquitous and Subjective Data. Becker, Martin; Mueller, Juergen; Hotho, Andreas; Stumme, Gerd (2013). New York, NY, USA.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]
   
  An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.
  @inproceedings{mueller-2013a, abstract = {An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.}, author = {Becker, Martin and Mueller, Juergen and Hotho, Andreas and Stumme, Gerd}, booktitle = {1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland &ndash; September 9, 2013. Proceedings}, keywords = {2013 everyaware from:hotho myown platform workshop}, note = {Accepted for publication}, pages = {New York, NY, USA}, publisher = {ACM}, title = {A Generic Platform for Ubiquitous and Subjective Data}, year = 2013 }
  %0 Conference Paper %1 mueller-2013a %A Becker, Martin %A Mueller, Juergen %A Hotho, Andreas %A Stumme, Gerd %B 1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings %D 2013 %I ACM %P New York, NY, USA %T A Generic Platform for Ubiquitous and Subjective Data %X An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.
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  Tag Recommendations for SensorFolkSonomies. Mueller, Juergen; Doerfel, Stephan; Becker, Martin; Hotho, Andreas; Stumme, Gerd (2013). (Vol. 1066)
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.
  @inproceedings{mueller2013recommendations, abstract = {With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.}, address = {Aachen, Germany}, author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd}, booktitle = {Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China &ndash; October 12-16, 2013. Proceedings}, keywords = {2013 everyaware folksonomy from:hotho myown recommender research:recommender research:recommender:selected sensor tag}, publisher = {CEUR-WS}, title = {Tag Recommendations for SensorFolkSonomies}, volume = 1066, year = 2013 }
  %0 Conference Paper %1 mueller2013recommendations %A Mueller, Juergen %A Doerfel, Stephan %A Becker, Martin %A Hotho, Andreas %A Stumme, Gerd %B Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings %C Aachen, Germany %D 2013 %I CEUR-WS %T Tag Recommendations for SensorFolkSonomies %U http://ceur-ws.org/Vol-1066/ %V 1066 %X With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.
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  Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme Doerfel, Stephan; Hotho, Andreas; Kartal-Aydemir, Aliye; Roßnagel, Alexander; Stumme, Gerd (2013). Vieweg + Teubner Verlag.
  [ BibTeX ] [ EndNote ] [ URL ]
   
  @book{doerfel2013informationelle, author = {Doerfel, Stephan and Hotho, Andreas and Kartal-Aydemir, Aliye and Roßnagel, Alexander and Stumme, Gerd}, keywords = {2013 from:hotho info20 l3s myown selbstbestimmung}, publisher = {Vieweg + Teubner Verlag}, title = {Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme}, year = 2013 }
  %0 Book %1 doerfel2013informationelle %A Doerfel, Stephan %A Hotho, Andreas %A Kartal-Aydemir, Aliye %A Roßnagel, Alexander %A Stumme, Gerd %D 2013 %I Vieweg + Teubner Verlag %T Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme %U http://www.worldcat.org/search?qt=worldcat_org_all&q=9783642380556 %@ 9783642380556 3642380557
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  Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia. Singer, Philipp; Niebler, Thomas; Strohmaier, Markus; Hotho, Andreas in International Journal on Semantic Web and Information Systems (IJSWIS) (2013). 9(4) 41--70.
  [ Abstract ] [ BibTeX ] [ EndNote ] [ URL ] [ Download ]
   
  In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.
  @article{singer2013computing, abstract = {In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.}, author = {Singer, Philipp and Niebler, Thomas and Strohmaier, Markus and Hotho, Andreas}, journal = {International Journal on Semantic Web and Information Systems (IJSWIS)}, keywords = {2013 from:hotho myown navigational posts postsi relatedness semantic}, number = 4, pages = {41&ndash;70}, publisher = {IGI Global}, title = {Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia}, volume = 9, year = 2013 }
  %0 Journal Article %1 singer2013computing %A Singer, Philipp %A Niebler, Thomas %A Strohmaier, Markus %A Hotho, Andreas %D 2013 %I IGI Global %J International Journal on Semantic Web and Information Systems (IJSWIS) %N 4 %P 41--70 %R 10.4018/ijswis.2013100103 %T Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia %U http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijswis.2013100103 %V 9 %X In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.
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