piwik-script

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 [ nach oben ]

    • 1.
      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).
       
    • Comparison of Transformer... - Download
      2.
      Fischer, E., Zoller, D., Hotho, A.: Comparison of Transformer-Based Sequential Product Recommendation Models for the Coveo Data Challenge. SIGIR Workshop On eCommerce. (2021).
       
    • Detecting Scenes in Ficti... - Download
      3.
      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).
       
    • Assessing Media Bias in C... - Download
      4.
      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).
       
    • Self-Supervised Multi-Tas... - Download
      5.
      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).
       
    • Semi-Supervised Learning ... - Download
      6.
      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).
       
    • Density-based weighting f... - Download
      7.
      Steininger, M., Kobs, K., Davidson, P., Krause, A., Hotho, A.: Density-based weighting for imbalanced regression. Machine Learning. (2021).
       
    • Proximity dimensions and ... - Download
      8.
      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).
       
    • Anomaly Detection in Beeh... - Download
      9.
      Davidson, P., Steininger, M., Lautenschlager, F., Krause, A., Hotho, A.: Anomaly Detection in Beehives: An Algorithm Comparison, (2021).
       
    • A financial game with opp... - Download
      10.
      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).
       
    • Evaluating the multi-task... - Download
      11.
      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).
       
    • Do Different Deep Metric ... - Download
      12.
      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).
       
    • A Case Study on Sampling ... - Download
      13.
      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).
       
    • 14.
      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 [ nach oben ]

    • HarryMotions – Classify... - Download
      1.
      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).
       
    • Financial Fraud Detection... - Download
      2.
      Schlör, D., Ring, M., Krause, A., Hotho, A.: Financial Fraud Detection with Improved Neural Arithmetic Logic Units. (2020).
       
    • 3.
      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).
       
    • 4.
      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).
       
    • 5.
      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).
       
    • Deep Learning for Climate... - Download
      6.
      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).
       
    • NICER — Aesthetic Image... - Download
      7.
      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).
       
    • Towards Predicting the Su... - Download
      8.
      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).
       
    • Where to Submit? Helping ... - Download
      9.
      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).
       
    • Evaluating the multi-task... - Download
      10.
      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).
       
    • iNALU: Improved Neural Ar... - Download
      11.
      Schlör, D., Ring, M., Hotho, A.: iNALU: Improved Neural Arithmetic Logic Unit. Frontiers in Artificial Intelligence. 3, 71 (2020).
       
    • LM4KG: Improving Common S... - Download
      12.
      Omeliyanenko, J., Zehe, A., Hettinger, L., Hotho, A.: LM4KG: Improving Common Sense Knowledge Graphs with Language Models. International Semantic Web Conference. Springer (2020).
       
    • Integrating Keywords into... - Download
      13.
      Fischer, E., Zoller, D., Dallmann, A., Hotho, A.: Integrating Keywords into BERT4Rec for Sequential Recommendation. KI 2020: Advances in Artificial Intelligence (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).
       
    • Improving Sentiment Analy... - Download
      15.
      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).
       
    • 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).
       
    • Evaluation of post-hoc XA... - Download
      17.
      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).
       
    • 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).
       
    • Anomaly Detection in Beeh... - Download
      21.
      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).
       
    • 22.
      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
      23.
      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
      24.
      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).
       
    • 25.
      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).
       

    2019 [ nach oben ]

    • On the Right Track! Analy... - Download
      1.
      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).
       
    • Team Xenophilius Lovegood... - Download
      2.
      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).
       
    • Flow-based network traffi... - Download
      3.
      Ring, M., Schlör, D., Landes, D., Hotho, A.: Flow-based network traffic generation using Generative Adversarial Networks. Computers & Security. 82, 156–172 (2019).
       
    • Detection of Scenes in Fi... - Download
      4.
      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).
       
    • 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).
       
    • 6.
      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).
       
    • Solving Mathematical Exer... - Download
      7.
      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).
       
    • 8.
      Wunderlich, S., Ring, M., Landes, D., Hotho, A.: Comparison of System Call Representations for Intrusion Detection. (2019).
       

    2018 [ nach oben ]

    • Adaptive kNN Using Expect... - Download
      1.
      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).
       
    • Analysing Direct Speech i... - Download
      2.
      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
      3.
      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).
       
    • ClaiRE at SemEval-2018 Ta... - Download
      4.
      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).
       
    • Burrows Zeta: Varianten u... - Download
      5.
      Schöch, C., Calvo, J., Zehe, A., Hotho, A.: Burrows Zeta: Varianten und Evaluation. DHd 2018 (2018).
       
    • Healing Time Correlates W... - Download
      6.
      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).
       
    • 7.
      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).
       
    • 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).
       
    • A White-Box Model for Det... - Download
      9.
      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).
       
    • 10.
      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).
       
    • 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 [ nach oben ]

    • 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 [ nach oben ]

    • 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
      2.
      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
      3.
      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
      4.
      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
      5.
      Hettinger, L., Jannidis, F., Reger, I., Hotho, A.: Significance Testing for the Classification of Literary Subgenres. DH 2016 (2016).
       
    • Classification of Literar... - Download
      6.
      Hettinger, L., Jannidis, F., Reger, I., Hotho, A.: Classification of Literary Subgenres. DHd 2016 (2016).
       
    • Prediction of Happy Endin... - Download
      7.
      Zehe, A., Becker, M., Hettinger, L., Hotho, A., Reger, I., Jannidis, F.: Prediction of Happy Endings in German Novels. In: Cellier, P., Charnois, T., Hotho, A., Matwin, S., Moens, M.-F., and Toussaint, Y. (eds.) Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing 2016. pp. 9–16 (2016).
       
    • Extracting Semantics from... - Download
      8.
      Dallmann, A., Niebler, T., Lemmerich, F., Hotho, A.: Extracting Semantics from Random Walks on Wikipedia: Comparing learning and counting methods. In: West, R., Zia, L., Taraborelli, D., and Leskovec, J. (eds.) Wiki Workshop@ICWSM (2016).
       
    • SparkTrails: A MapReduce ... - Download
      9.
      Becker, M., Mewes, H., Hotho, A., Dimitrov, D., Lemmerich, F., Strohmaier, M.: SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails. In: Bourdeau, J., Hendler, J., Nkambou, R., Horrocks, I., and Zhao, B.Y. (eds.) WWW (Companion Volume). pp. 17–18. ACM (2016).
       
    • FolkTrails: Interpreting ... - Download
      10.
      Niebler, T., Becker, M., Zoller, D., Doerfel, S., Hotho, A.: FolkTrails: Interpreting Navigation Behavior in a Social Tagging System. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ACM, New York, NY, USA (2016).
       
    • Creation of Specific Flow... - Download
      11.
      Otto, F., Ring, M., Landes, D., Hotho, A.: Creation of Specific Flow-Based Training Data Sets for Usage Behaviour Classification. ECCWS2016-Proceedings fo the 15th European Conference on Cyber Warfare and Security. p. 437. Academic Conferences and publishing limited (2016).
       
    • MixedTrails: Bayesian Hyp... - Download
      12.
      Becker, M., Lemmerich, F., Singer, P., Strohmaier, M., Hotho, A.: MixedTrails: Bayesian Hypotheses Comparison on Heterogeneous Sequential Data, http://arxiv.org/abs/1612.07612, (2016).