piwik-script

Deutsch Intern
    Data Science Chair

    Publications

    [ 2021 ] [ 2020 ] [ 2019 ] [ 2018 ] [ 2017 ] [ 2016 ] [ 2015 ] [ 2014 ] [ 2013 ] [ 2012 ] [ 2011 ] [ 2010 ] [ 2009 ] [ 2008 ] [ 2007 ] [ 2006 ] [ 2005 ] [ 2004 ] [ 2003 ] [ 2002 ] [ 2001 ] [ 2000 ]

    2021 [ to top ]

    • The FairyNet Corpus - Cha... - Download
      1.
      Schmidt, D., Zehe, A., Lorenzen, J., Sergel, L., Düker, S., Krug, M., Puppe, F.: The FairyNet Corpus - Character Networks for German Fairy Tales. Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. pp. 49–56. Association for Computational Linguistics, Punta Cana, Dominican Republic (online) (2021).
       
    • Do Different Deep Metric ... - Download
      2.
      Kobs, K., Steininger, M., Dulny, A., Hotho, A.: Do Different Deep Metric Learning Losses Lead to Similar Learned Features?. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). 10644–10654 (2021).
       
    • 3.
      Ring, M., Schlör, D., Wunderlich, S., Landes, D., Hotho, A.: Malware detection on windows audit logs using LSTMs. Computers & Security. 109, 102389 (2021).
       
    • CoBERT: Scientific Collab... - Download
      4.
      Koopmann, T., Kobs, K., Herud, K., Hotho, A.: CoBERT: Scientific Collaboration Prediction via Sequential Recommendation. 2021 International Conference on Data Mining Workshops (ICDMW). pp. 45–54 (2021).
       
    • DETECTING PRESENCE OF SPE... - Download
      5.
      Janetzky, P., Davidson, P., Steininger, M., Krause, A., Hotho, A.: DETECTING PRESENCE OF SPEECH IN ACOUSTIC DATA OBTAINED FROM BEEHIVES. DCASE Workshop. (2021).
       
    • Shared Task on Scene Segm... - Download
      6.
      Zehe, A., Konle, L., Guhr, S., Dümpelmann, L., Gius, E., Hotho, A., Jannidis, F., Kaufmann, L., Krug, M., Puppe, F., Reiter, N., Schreiber, A.: Shared Task on Scene Segmentation @ KONVENS 2021. Shared Task on Scene Segmentation @ KONVENS 2021. pp. 1–21 (2021).
       
    • 7.
      Hotho, A., Blomqvist, E., Dietze, S., Fokoue, A., Ding, Y., Barnaghi, P.M., Haller, A., Dragoni, M., Alani, H. eds.: The Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24-28, 2021, Proceedings. Springer (2021).
       
    • 8.
      Davidson, P., Buckermann, F., Steininger, M., Krause, A., Hotho, A.: Semi-unsupervised Learning: An In-depth Parameter Analysis. In: Edelkamp, S., Möller, R., and Rueckert, E. (eds.) KI 2021: Advances in Artificial Intelligence. pp. 51–66. Springer International Publishing, Cham (2021).
       
    • Anomaly Detection in Beeh... - Download
      9.
      Davidson, P., Steininger, M., Lautenschlager, F., Krause, A., Hotho, A.: Anomaly Detection in Beehives: An Algorithm Comparison, (2021).
       
    • 10.
      Dallmann, A., Kohlmann, J., Zoller, D., Hotho, A.: Sequential Item Recommendation in the MOBA Game Dota 2. 2021 International Conference on Data Mining Workshops (ICDMW). pp. 10–17 (2021).
       
    • Density-based weighting f... - Download
      11.
      Steininger, M., Kobs, K., Davidson, P., Krause, A., Hotho, A.: Density-based weighting for imbalanced regression. Machine Learning. (2021).
       
    • Evaluating the multi-task... - Download
      12.
      Dulny, A., Steininger, M., Lautenschlager, F., Krause, A., Hotho, A.: Evaluating the multi-task learning approach for land use regression modelling of air pollution. Journal of Physics: Conference Series. 1834, 012004 (2021).
       
    • A financial game with opp... - Download
      13.
      Tritscher, J., Krause, A., Schlör, D., Gwinner, F., von Mammen, S., Hotho, A.: A financial game with opportunities for fraud. IEE COG 2021. 2021, (2021).
       
    • A Case Study on Sampling ... - Download
      14.
      Dallmann, A., Zoller, D., Hotho, A.: A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models. Fifteenth ACM Conference on Recommender Systems. ACM (2021).
       
    • Comparison of Transformer... - Download
      15.
      Fischer, E., Zoller, D., Hotho, A.: Comparison of Transformer-Based Sequential Product Recommendation Models for the Coveo Data Challenge. SIGIR Workshop On eCommerce. (2021).
       
    • Semi-Supervised Learning ... - Download
      16.
      Kobs, K., Schäfer, C., Steininger, M., Krause, A., Baumhauer, R., Paeth, H., Hotho, A.: Semi-Supervised Learning for Grain Size Distribution Interpolation. Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10--15, 2021, Proceedings, Part VI. pp. 34–44. Springer International Publishing (2021).
       
    • Self-Supervised Multi-Tas... - Download
      17.
      Pfister, J., Kobs, K., Hotho, A.: Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. pp. 816–825 (2021).
       
    • Assessing Media Bias in C... - Download
      18.
      Sales, A., Zehe, A., Marinho, L.B., Veloso, A., Hotho, A., Omeliyanenko, J.: Assessing Media Bias in Cross-Linguistic and Cross-National Populations. Proceedings of the International AAAI Conference on Web and Social Media. 15, 561–572 (2021).
       
    • Proximity dimensions and ... - Download
      19.
      Koopmann, T., Stubbemann, M., Kapa, M., Paris, M., Buenstorf, G., Hanika, T., Hotho, A., Jäschke, R., Stumme, G.: Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research. Scientometrics. (2021).
       
    • Detecting Scenes in Ficti... - Download
      20.
      Zehe, A., Konle, L., Dümpelmann, L., Gius, E., Hotho, A., Jannidis, F., Kaufmann, L., Krug, M., Puppe, F., Reiter, N., Schreiber, A., Wiedmer, N.: Detecting Scenes in Fiction: A new Segmentation Task. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. ACL (2021).
       
    • 21.
      Dulny, A., Hotho, A., Krause, A.: NeuralPDE: Modelling Dynamical Systems from Data, http://arxiv.org/abs/2111.07671, (2021).
       
    • 22.
      Buckermann, F., Klement, N., Beyer, O., Hütten, A., Hammer, B.: Automating the optical identification of abrasive wear on electrical contact pins. at - Automatisierungstechnik. 69, 903–914 (2021).
       

    2020 [ to top ]

    • Integrating Keywords into... - Download
      1.
      Fischer, E., Zoller, D., Dallmann, A., Hotho, A.: Integrating Keywords into BERT4Rec for Sequential Recommendation. KI 2020: Advances in Artificial Intelligence (2020).
       
    • NICER — Aesthetic Image... - Download
      2.
      Fischer, M., Kobs, K., Hotho, A.: NICER — Aesthetic Image Enhancement with Humans in the Loop. ACHI 2020: The Thirteenth International Conference on Advances in Computer-Human Interactions. pp. 357–362 (2020).
       
    • Where to Submit? Helping ... - Download
      3.
      Kobs, K., Koopmann, T., Zehe, A., Fernes, D., Krop, P., Hotho, A.: Where to Submit? Helping Researchers to Choose the Right Venue. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings. pp. 878–883. Association for Computational Linguistics, Online (2020).
       
    • Towards Predicting the Su... - Download
      4.
      Kobs, K., Potthast, M., Wiegmann, M., Zehe, A., Stein, B., Hotho, A.: Towards Predicting the Subscription Status of Twitch.tv Users. Proceedings of ECML-PKDD 2020 ChAT Discovery Challenge on Chat Analytics for Twitch. (2020).
       
    • Deep Learning for Climate... - Download
      5.
      Steininger, M., Abel, D., Ziegler, K., Krause, A., Paeth, H., Hotho, A.: Deep Learning for Climate Model Output Statistics. Tackling Climate Change with Machine Learning Workshop at NeurIPS 2020. (2020).
       
    • 6.
      Brefeld, U., Fromont, Élisa, Hotho, A., Knobbe, A.J., Maathuis, M.H., Robardet, C. eds.: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II. Springer (2020).
       
    • 7.
      Brefeld, U., Fromont, Élisa, Hotho, A., Knobbe, A.J., Maathuis, M.H., Robardet, C. eds.: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I. Springer (2020).
       
    • 8.
      Brefeld, U., Fromont, Élisa, Hotho, A., Knobbe, A.J., Maathuis, M.H., Robardet, C. eds.: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part III. Springer (2020).
       
    • iNALU: Improved Neural Ar... - Download
      9.
      Schlör, D., Ring, M., Hotho, A.: iNALU: Improved Neural Arithmetic Logic Unit. Frontiers in Artificial Intelligence. 3, 71 (2020).
       
    • 10.
      Stubbemann, M., Koopmann, T.: The German and International AI Network Data Set. (2020).
       
    • 11.
      Tritscher, J., Ring, M., Schlr, D., Hettinger, L., Hotho, A.: Evaluation of Post-hoc XAI Approaches Through Synthetic Tabular Data. In: Helic, D., Leitner, G., Stettinger, M., Felfernig, A., and Ra’s, Z.W. (eds.) Foundations of Intelligent Systems. pp. 422–430. Springer International Publishing, Cham (2020).
       
    • Financial Fraud Detection... - Download
      12.
      Schlör, D., Ring, M., Krause, A., Hotho, A.: Financial Fraud Detection with Improved Neural Arithmetic Logic Units. (2020).
       
    • Improving Sentiment Analy... - Download
      13.
      Schlör, D., Zehe, A., Kobs, K., Veseli, B., Westermeier, F., Brübach, L., Roth, D., Latoschik, M.E., Hotho, A.: Improving Sentiment Analysis with Biofeedback Data. Proceedings of LREC2020 Workshop ``People in language, vision and the mind’’ (ONION2020). pp. 28–33. European Language Resources Association (ELRA), Marseille, France (2020).
       
    • 14.
      Kobs, K., Zehe, A., Bernstetter, A., Chibane, J., Pfister, J., Tritscher, J., Hotho, A.: Emote-Controlled: Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels. ACM Transactions on Social Computing. 3, 1–34 (2020).
       
    • Evaluation of post-hoc XA... - Download
      15.
      Tritscher, J., Ring, M., Schlör, D., Hettinger, L., Hotho, A.: Evaluation of post-hoc XAI approaches through synthetic tabular data. International Symposium on Methodologies for Intelligent Systems. (2020).
       
    • Emote-Controlled: Obtaini... - Download
      16.
      Kobs, K., Zehe, A., Bernstetter, A., Chibane, J., Pfister, J., Tritscher, J., Hotho, A.: Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels. ACM Transactions on Social Computing. (2020).
       
    • LM4KG: Improving Common S... - Download
      17.
      Omeliyanenko, J., Zehe, A., Hettinger, L., Hotho, A.: LM4KG: Improving Common Sense Knowledge Graphs with Language Models. International Semantic Web Conference. Springer (2020).
       
    • SimLoss: Class Similariti... - Download
      18.
      Kobs, K., Steininger, M., Zehe, A., Lautenschlager, F., Hotho, A.: SimLoss: Class Similarities in Cross Entropy, http://arxiv.org/abs/2003.03182, (2020).
       
    • MapLUR: Exploring a New P... - Download
      19.
      Steininger, M., Kobs, K., Zehe, A., Lautenschlager, F., Becker, M., Hotho, A.: MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images. ACM Trans. Spatial Algorithms Syst. 6, (2020).
       
    • OpenLUR: Off-the-shelf ai... - Download
      20.
      Lautenschlager, F., Becker, M., Kobs, K., Steininger, M., Davidson, P., Krause, A., Hotho, A.: OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning. Atmospheric Environment. 233, 117535 (2020).
       
    • HarryMotions – Classify... - Download
      21.
      Zehe, A., Arns, J., Hettinger, L., Hotho, A.: HarryMotions – Classifying Relationships in Harry Potter based on Emotion Analysis. 5th SwissText & 16th KONVENS Joint Conference (2020).
       
    • Anomaly Detection in Beeh... - Download
      22.
      Davidson, P., Steininger, M., Lautenschlager, F., Kobs, K., Krause, A., Hotho, A.: Anomaly Detection in Beehives using Deep Recurrent Autoencoders. Proceedings of the 9th International Conference on Sensor Networks (SENSORNETS 2020). pp. 142–149. SCITEPRESS – Science and Technology Publications, Lda (2020).
       
    • 23.
      Bauer, A., Züfle, M., Herbst, N., Zehe, A., Hotho, A., Kounev, S.: Time Series Forecasting for Self-Aware Systems. Proceedings of the IEEE. 1–26 (2020).
       
    • Smartwatch-Derived Data a... - Download
      24.
      Davidson, P., Düking, P., Zinner, C., Sperlich, B., Hotho, A.: Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study. Sensors. (2020).
       
    • Improving Sentiment Analy... - Download
      25.
      Schlör, D., Zehe, A., Kobs, K., Veseli, B., Westermeier, F., Brübach, L., Roth, D., Latoschik, M.E., Hotho, A.: Improving Sentiment Analysis with Biofeedback Data. Proceedings of the Workshop on peOple in laNguage, vIsiOn and the miNd (ONION) (2020).
       
    • Evaluating the multi-task... - Download
      26.
      Dulny, A., Steininger, M., Lautenschlager, F., Krause, A., Hotho, A.: Evaluating the multi-task learning approach for land use regression modelling of air pollution. International Conference on Frontiers of Artificial Intelligence and Machine Learning. IASED (2020).
       

    2019 [ to top ]

    • 1.
      Ring, M., Wunderlich, S., Scheuring, D., Landes, D., Hotho, A.: A survey of network-based intrusion detection data sets. Comput. Secur. 86, 147–167 (2019).
       
    • 2.
      Wunderlich, S., Ring, M., Landes, D., Hotho, A.: Comparison of System Call Representations for Intrusion Detection. (2019).
       
    • Solving Mathematical Exer... - Download
      3.
      Wankerl, S., Götz, G., Hotho, A.: Solving Mathematical Exercises: Prediction of Students’ Success. In: Jäschke, R. and Weidlich, M. (eds.) LWDA. pp. 190–194. CEUR-WS.org (2019).
       
    • On the Right Track! Analy... - Download
      4.
      Koopmann, T., Dallmann, A., Hettinger, L., Niebler, T., Hotho, A.: On the Right Track! Analysing and Predicting Navigation Success in Wikipedia. Proceedings of the 30th ACM Conference on Hypertext and Social Media. pp. 143–152. ACM, Hof, Germany (2019).
       
    • EClaiRE: Context Matters!... - Download
      5.
      Hettinger, L., Zehe, A., Dallmann, A., Hotho, A.: EClaiRE: Context Matters! – Comparing Word Embeddings for Relation Classification. In: David, K., Geihs, K., Lange, M., and Stumme, G. (eds.) INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft. pp. 191–204. Gesellschaft für Informatik e.V., Bonn (2019).
       
    • Detection of Scenes in Fi... - Download
      6.
      Gius, E., Jannidis, F., Krug, M., Zehe, A., Hotho, A., Puppe, F., Krebs, J., Reiter, N., Wiedmer, N., Konle, L.: Detection of Scenes in Fiction. Proceedings of Digital Humanities 2019 (2019).
       
    • Flow-based network traffi... - Download
      7.
      Ring, M., Schlör, D., Landes, D., Hotho, A.: Flow-based network traffic generation using Generative Adversarial Networks. Computers & Security. 82, 156–172 (2019).
       
    • Team Xenophilius Lovegood... - Download
      8.
      Zehe, A., Hettinger, L., Ernst, S., Hauptmann, C., Hotho, A.: Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks. Proceedings of The 13th International Workshop on Semantic Evaluation. Association for Computational Linguistics (2019).
       

    2018 [ to top ]

    • A White-Box Model for Det... - Download
      1.
      Zehe, A., Schlör, D., Henny-Krahmer, U., Becker, M., Hotho, A.: A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels. DH. ADHO (2018).
       
    • Healing Time Correlates W... - Download
      2.
      Werdin, F., Tenenhaus, M., Becker, M., Rennekampff, H.-O.: Healing Time Correlates With the Quality of Scaring: Results From a Prospective Randomized Control Donor Site Trial. Dermatologic Surgery. 44, 521–527 (2018).
       
    • 3.
      Schwarzmann, S., Blenk, A., Dobrijevic, O., Jarschel, M., Hotho, A., Zinner, T., Wamser, F.: Big-Data Helps SDN to Improve Application Specific Quality of Service. Big Data and Software Defined Networks. IET (2018).
       
    • Analysing Direct Speech i... - Download
      4.
      Jannidis, F., Konle, L., Zehe, A., Hotho, A., Krug, M.: Analysing Direct Speech in German Novels. DHd 2018 (2018).
       
    • ClaiRE at SemEval-2018 Ta... - Download
      5.
      Hettinger, L., Dallmann, A., Zehe, A., Niebler, T., Hotho, A.: ClaiRE at SemEval-2018 Task 7 - Extended Version, http://arxiv.org/abs/1804.05825, (2018).
       
    • ClaiRE at SemEval-2018 Ta... - Download
      6.
      Hettinger, L., Dallmann, A., Zehe, A., Niebler, T., Hotho, A.: ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings. Proceedings of International Workshop on Semantic Evaluation (SemEval-2018). , New Orleans, LA, USA (2018).
       
    • Burrows Zeta: Varianten u... - Download
      7.
      Schöch, C., Calvo, J., Zehe, A., Hotho, A.: Burrows Zeta: Varianten und Evaluation. DHd 2018 (2018).
       
    • 8.
      Navarro Bullock, B., Hotho, A., Stumme, G.: Accessing Information with Tags: Search and Ranking. In: Brusilovsky, P. and He, D. (eds.) Social Information Access: Systems and Technologies. pp. 310–343. Springer International Publishing, Cham (2018).
       
    • 9.
      Schöch, C., Schlör, D., Zehe, A., Gebhard, H., Becker, M., Hotho, A.: Burrows’ Zeta: Exploring and Evaluating Variants and Parameters. DH. pp. 274–277 (2018).
       
    • Adaptive kNN Using Expect... - Download
      10.
      Kibanov, M., Becker, M., Müller, J., Atzmüller, M., Hotho, A., Stumme, G.: Adaptive kNN Using Expected Accuracy for Classification of Geo-spatial Data. Proceedings of the 33rd Annual ACM Symposium on Applied Computing. pp. 857–865. ACM, Pau, France (2018).
       
    • Air Trails -- Urban Air Q... - Download
      11.
      Becker, M., Lautenschlager, F., Hotho, A.: Air Trails -- Urban Air Quality Campaign Exploration Patterns. (2018).
       
    • pysubgroup: Easy-to-Use S... - Download
      12.
      Lemmerich, F., Becker, M.: pysubgroup: Easy-to-Use Subgroup Discovery in Python. In: Brefeld, U., Curry, E., Daly, E., MacNamee, B., Marascu, A., Pinelli, F., Berlingerio, M., and Hurley, N. (eds.) ECML/PKDD (3). pp. 658–662. Springer (2018).
       
    • 13.
      Ring, M., Schlör, D., Landes, D., Hotho, A.: Flow-based Network Traffic Generation using Generative Adversarial Networks. CoRR. abs/1810.07795, (2018).
       
    • 14.
      Ring, M., Landes, D., Hotho, A.: Detection of slow port scans in flow-based network traffic. PLOS ONE. 13, 1–18 (2018).
       
    • EveryAware Gears: A Tool ... - Download
      15.
      Lautenschlager, F., Becker, M., Steininger, M., Hotho, A.: EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data. In: Burghardt, D., Chen, S., Andrienko, G., Andrienko, N., Purves, R., and Diehl, A. (eds.) Proceedings of VGI Geovisual Analytics Workshop, colocated with BDVA 2018. KOPS (2018).
       

    2017 [ to top ]

    • MixedTrails: Bayesian hyp... - Download
      1.
      Becker, M., Lemmerich, F., Singer, P., Strohmaier, M., Hotho, A.: MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data. Data Mining and Knowledge Discovery. (2017).
       
    • Applications for Environm... - Download
      2.
      Atzmueller, M., Becker, M., Molino, A., Mueller, J., Peters, J., S^irbu, A.: Applications for Environmental Sensing in EveryAware. Participatory Sensing, Opinions and Collective Awareness. pp. 135–155. Springer (2017).
       
    • Flow-based benchmark data... - Download
      3.
      Ring, M., Wunderlich, S., Grüdl, D., Landes, D., Hotho, A.: Flow-based benchmark data sets for intrusion detection. Proceedings of the 16th European Conference on Cyber Warfare and Security. pp. 361–369 (2017).
       
    • Comparing Hypotheses Abou... - Download
      4.
      Lemmerich, F., Singer, P., Becker, M., Espin-Noboa, L., Dimitrov, D., Helic, D., Hotho, A., Strohmaier, M.: Comparing Hypotheses About Sequential Data: A Bayesian Approach and Its Applications. Joint European Conference on Machine Learning and Knowledge Discovery in Databases. pp. 354–357. Springer (2017).
       
    • IP2Vec: Learning Similari... - Download
      5.
      Ring, M., Landes, D., Dallmann, A., Hotho, A.: IP2Vec: Learning Similarities Between IP Addresses. 2017 IEEE International Conference on Data Mining Workshops (ICDMW). 657–666 (2017).
       
    • Neutralising the Authoria... - Download
      6.
      Tello, J.C., Schlör, D., Henny-Krahmer, U., Schöch, C.: Neutralising the Authorial Signal in Delta by Penalization: Stylometric Clustering of Genre in Spanish Novels. In: Lewis, R., Raynor, C., Forest, D., Sinatra, M., and Sinclair, S. (eds.) DH. Alliance of Digital Humanities Organizations (ADHO) (2017).
       
    • Creation of Flow-Based Da... - Download
      7.
      Ring, M., Wunderlich, S., Grüdl, D., Landes, D., Hotho, A.: Creation of Flow-Based Data Sets for Intrusion Detection. Journal of Information Warfare. 16, 41–54 (2017).
       
    • Participatory sensing, op... - Download
      8.
      Loreto, V., Haklay, M., Hotho, A., Servedio, V.C.P., Stumme, G., Theunis, J., Tria, F. eds.: Participatory sensing, opinions and collective awareness. Springer (2017).
       
    • A Toolset for Intrusion a... - Download
      9.
      Ring, M., Wunderlich, S., Grüdl, D., Landes, D., Hotho, A.: A Toolset for Intrusion and Insider Threat Detection. In: Palomares Carrascosa, I., Kalutarage, H.K., and Huang, Y. (eds.) Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications. pp. 3–31. Springer International Publishing, Cham (2017).
       
    • Learning Semantic Related... - Download
      10.
      Niebler, T., Becker, M., Pölitz, C., Hotho, A.: Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning. ISWC’17 (2017).
       
    • Learning Semantic Related... - Download
      11.
      Niebler, T., Becker, M., Pölitz, C., Hotho, A.: Learning Semantic Relatedness From Human Feedback Using Metric Learning, http://arxiv.org/abs/1705.07425, (2017).
       
    • Leveraging User-Interacti... - Download
      12.
      Zoller, D., Doerfel, S., Pölitz, C., Hotho, A.: Leveraging User-Interactions for Time-Aware Tag Recommendations. Proceedings of the Workshop on Temporal Reasoning in Recommender Systems (2017).
       
    • Sedentary Behavior among ... - Download
      13.
      Sperlich, B., Becker, M., Hotho, A., Wallmann-Sperlich, B., Sareban, M., Winkert, K., Steinacker, J.M., Treff, G.: Sedentary Behavior among National Elite Rowers during Off-Training—A Pilot Study. Frontiers in Physiology. 8, 655 (2017).
       
    • Collective Sensing Platfo... - Download
      14.
      Atzmueller, M., Becker, M., Mueller, J.: Collective Sensing Platforms. Participatory Sensing, Opinions and Collective Awareness. pp. 115–133. Springer (2017).
       
    • Mining social semantics o... - Download
      15.
      Hotho, A., Jaeschke, R., Lerman, K.: Mining social semantics on the social web. Semantic Web. 8, 623–624 (2017).
       
    • 16.
      Singer, P., Helic, D., Hotho, A., Strohmaier, M.: A Bayesian Method for Comparing Hypotheses About Human Trails. ACM Trans. Web. 11, 14:1–14:29 (2017).
       
    • Experimental Assessment o... - Download
      17.
      Gravino, P., S^irbu, A., Becker, M., Servedio, V.D., Loreto, V.: Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson. Participatory Sensing, Opinions and Collective Awareness. pp. 337–362. Springer (2017).
       
    • Learning Word Embeddings ... - Download
      18.
      Niebler, T., Hahn, L., Hotho, A.: Learning Word Embeddings from Tagging Data: A methodological comparison. Proceedings of the LWDA (2017).
       
    • Eleven-Week Preparation I... - Download
      19.
      Treff, G., Winkert, K., Sareban, M., Steinacker, J.M., Becker, M., Sperlich, B.: Eleven-Week Preparation Involving Polarized Intensity Distribution Is Not Superior to Pyramidal Distribution in National Elite Rowers. Frontiers in Physiology. 8, 515 (2017).
       
    • Towards Sentiment Analysi... - Download
      20.
      Zehe, A., Becker, M., Jannidis, F., Hotho, A.: Towards Sentiment Analysis on German Literature. Presented at the (2017).
       
    • Improving Session Recomme... - Download
      21.
      Dallmann, A., Grimm, A., Pölitz, C., Zoller, D., Hotho, A.: Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time. CoRR. abs/1706.10231, (2017).
       

    2016 [ to top ]

    • Posted, Visited, Exported... - Download
      1.
      Zoller, D., Doerfel, S., Jäschke, R., Stumme, G., Hotho, A.: Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy. Journal of Informetrics. 10, 732–749 (2016).
       
    • Comparison of non-invasiv... - Download
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      Düking, P., Hotho, A., Fuss, F.K., Holmberg, H.-C., Sperlich, B.: Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies. Frontiers in Physiology. 7, (2016).
       
    • Extracting Semantics from... - Download
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      Niebler, T., Schlör, D., Becker, M., Hotho, A.: Extracting Semantics from Unconstrained Navigation on Wikipedia. KI. 30, 163–168 (2016).
       
    • What Users Actually do in... - Download
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      Doerfel, S., Zoller, D., Singer, P., Niebler, T., Hotho, A., Strohmaier, M.: What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy. ACM Transactions on the Web. 10, 14:1–14:32 (2016).
       
    • Significance Testing for ... - Download
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      Hettinger, L., Jannidis, F., Reger, I., Hotho, A.: Significance Testing for the Classification of Literary Subgenres. DH 2016 (2016).