Prof. Dr. Felix Naumann



  • Jain, N., Krestel, R.: Learning Fine-Grained Semantics for Multi-Relational Data.International Semantic Web Conference, 2020 Posters amd Demos (2020).
  • Jain, N.: Domain-Specific Knowledge Graph Construction for Semantic Analysis.Extended Semantic Web Conference (ESWC 2020) Ph.D. Symposium (2020).
  • Risch, J., Krestel, R.: Toxic Comment Detection in Online Discussions. In: Agarwal, B., Nayak, R., Mittal, N., and Patnaik, S. (eds.) Deep Learning-Based Approaches for Sentiment Analysis. pp. 85-109. Springer (2020).
  • Hacker, P., Krestel, R., Grundmann, S., Naumann, F.: Explainable AI under Contract and Tort Law: Legal Incentives and Technical Challenges.Artificial Intelligence and Law. (2020).
  • Repke, T., Krestel, R.: Visualising Large Document Collections by Jointly Modeling Text and Network Structure.Proceedings of the Joint Conference on Digital Libraries (JCDL). (2020).
  • Risch, J., Krestel, R.: Top Comment or Flop Comment? Predicting and Explaining User Engagement in Online News Discussions.Proceedings of the International Conference on Web and Social Media (ICWSM). pp. 579-589. AAAI (2020).
  • Jain, N., Bartz, C., Krestel, R.: Automatic Matching of Paintings and Descriptions in Art-Historic Archives using Multimodal Analysis.1st International Workshop on Artificial Intelligence for Historical Image Enrichment and Access (AI4HI-2020), co-located with LREC 2020 conference (2020).
  • Repke, T., Krestel, R.: Exploration Interface for Jointly Visualised Text and Graph Data.International Conference on Intelligent User Interfaces Companion (IUI '20). (2020).
  • Risch, J., Krestel, R.: Bagging BERT Models for Robust Aggression Identification.Proceedings of the Workshop on Trolling, Aggression and Cyberbullying (TRAC@LREC). pp. 55-61. European Language Resources Association (ELRA) (2020).
  • Ehmüller, J., Kohlmeyer, L., McKee, H., Paeschke, D., Repke, T., Krestel, R., Naumann, F.: Sense Tree: Discovery of New Word Senses with Graph-based Scoring.Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen" (LWDA). p. 1--12 (2020).
  • Bejnordi, A.E., Krestel, R.: Dynamic Channel and Layer Gating in Convolutional Neural Networks.Proceedings of the 43rd German Conference on Artificial Intelligence (KI 2020) (2020).
  • Risch, J., Garda, S., Krestel, R.: Hierarchical Document Classification as a Sequence Generation Task.Proceedings of the Joint Conference on Digital Libraries (JCDL). p. 147--155 (2020).
  • Risch, J., Krestel, R.: A Dataset of Journalists' Interactions with Their Readership: When Should Article Authors Reply to Reader Comments?Proceedings of the International Conference on Information and Knowledge Management (CIKM). ACM (2020).
  • Risch, J., Ruff, R., Krestel, R.: Explaining Offensive Language Detection.Journal for Language Technology and Computational Linguistics (JLCL).34,29-47 (2020).
  • Lazaridou, K., Löser, A., Mestre, M., Naumann, F.: Discovering Biased News Articles Leveraging Multiple Human Annotations.Proceedings of the Conference on Language Resources and Evaluation (LREC). pp. 1268–1277 (2020).
  • Risch, J., Ruff, R., Krestel, R.: Offensive Language Detection Explained.Proceedings of the Workshop on Trolling, Aggression and Cyberbullying (TRAC@LREC). pp. 137-143. European Language Resources Association (ELRA) (2020).


  • Risch, J., Stoll, A., Ziegele, M., Krestel, R.: hpiDEDIS at GermEval 2019: Offensive Language Identification using a German BERT model.Proceedings of the 15th Conference on Natural Language Processing (KONVENS). p. 403--408. German Society for Computational Linguistics & Language Technology, Erlangen, Germany (2019).
  • Jain, N., Krestel, R.: Who is Mona L.? Identifying Mentions of Artworks in Historical Archives.International Conference on Theory and Practice of Digital Libraries (TPDL 2019). p. 115--122. Springer (2019).
  • Risch, J., Krestel, R.: Measuring and Facilitating Data Repeatability in Web Science.Datenbank-Spektrum.19,117-126 (2019).
  • Risch, J., Krestel, R.: Domain-specific word embeddings for patent classification.Data Technologies and Applications.53,108-122 (2019).
  • Kellermeier, T., Repke, T., Krestel, R.: Mining Business Relationships from Stocks and News.MIDAS@ECML-PKDD. (2019).


  • Risch, J., Krestel, R.: Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom.Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (co-located with COLING). pp. 166-176 (2018).
  • Repke, T., Krestel, R.: Bringing Back Structure to Free Text Email Conversations with Recurrent Neural Networks.40th European Conference on Information Retrieval (ECIR 2018). Springer, Grenoble, France (2018).
  • Repke, T., Krestel, R.: Topic-aware Network Visualisation to Explore Large Email Corpora.International Workshop on Big Data Visual Exploration and Analytics (BigVis). (2018).
  • Risch, J., Krestel, R.: My Approach = Your Apparatus? Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections.Proceedings of the 18th ACM/IEEE Joint Conference on Digital Libraries (JCDL). pp. 283-292 (2018).
  • Lazaridou, K., Gruetze, T., Naumann, F.: Where in the World Is Carmen Sandiego? Detecting Person Locations via Social Media Discussions.Proceedings of the ACM Conference on Web Science. ACM (2018).
  • Ambroselli, C., Risch, J., Krestel, R., Loos, A.: Prediction for the Newsroom: Which Articles Will Get the Most Comments?Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). pp. 193-199. ACL, New Orleans, Louisiana, USA (2018).
  • Bunk, S., Krestel, R.: WELDA: Enhancing Topic Models by Incorporating Local Word Contexts.Joint Conference on Digital Libraries (JCDL 2018). ACM, Forth Worth, Texas, USA (2018).
  • Risch, J., Krestel, R.: Aggression Identification Using Deep Learning and Data Augmentation.Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (co-located with COLING). pp. 150-158 (2018).
  • van Aken, B., Risch, J., Krestel, R., Löser, A.: Challenges for Toxic Comment Classification: An In-Depth Error Analysis.Proceedings of the 2nd Workshop on Abusive Language Online (co-located with EMNLP). pp. 33-42 (2018).
  • Risch, J., Krestel, R.: Learning Patent Speak: Investigating Domain-Specific Word Embeddings.Proceedings of the Thirteenth International Conference on Digital Information Management (ICDIM). pp. 63-68 (2018).
  • Risch, J., Krebs, E., Löser, A., Riese, A., Krestel, R.: Fine-Grained Classification of Offensive Language.Proceedings of GermEval (co-located with KONVENS). pp. 38-44 (2018).
  • Risch, J., Garda, S., Krestel, R.: Book Recommendation Beyond the Usual Suspects: Embedding Book Plots Together with Place and Time Information.Proceedings of the 20th International Conference On Asia-Pacific Digital Libraries (ICADL). pp. 227-239 (2018).
  • Loster, M., Repke, T., Krestel, R., Naumann, F., Ehmueller, J., Feldmann, B., Maspfuhl, O.: The Challenges of Creating, Maintaining and Exploring Graphs of Financial Entities.Proceedings of the Fourth International Workshop on Data Science for Macro-Modeling (DSMM 2018). ACM (2018).
  • Repke, T., Krestel, R., Edding, J., Hartmann, M., Hering, J., Kipping, D., Schmidt, H., Scordialo, N., Zenner, A.: Beacon in the Dark: A System for Interactive Exploration of Large Email Corpora.Proceedings of the International Conference on Information and Knowledge Management (CIKM). p. 1--4. ACM (2018).


  • Gruetze, T., Krestel, R., Lazaridou, K., Naumann, F.: What was Hillary Clinton doing in Katy, Texas?Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, 3-7 April, 2017. ACM (2017).
  • Repke, T., Loster, M., Krestel, R.: Comparing Features for Ranking Relationships Between Financial Entities Based on Text.Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets. p. 12:1--12:2. ACM, New York, NY, USA (2017).
  • Risch, J., Krestel, R.: What Should I Cite? Cross-Collection Reference Recommendation of Patents and Papers.Proceedings of the International Conference on Theory and Practice of Digital Libraries (TPDL). pp. 40-46 (2017).
  • Lazaridou, K., Krestel, R., Naumann, F.: Identifying Media Bias by Analyzing Reported Speech.International Conference on Data Mining. IEEE (2017).
  • Krestel, R., Risch, J.: How Do Search Engines Work? A Massive Open Online Course with 4000 Participants.Proceedings of the Conference Lernen, Wissen, Daten, Analysen. pp. 259-271 (2017).
  • Zuo, Z., Loster, M., Krestel, R., Naumann, F.: Uncovering Business Relationships: Context-sensitive Relationship Extraction for Difficult Relationship Types.Proceedings of the Conference "Lernen, Wissen, Daten, Analysen" (LWDA) (2017).
  • Naumann, F., Krestel, R.: Das Fachgebiet „Informationssysteme“ am Hasso-Plattner-Institut.Datenbankspektrum.17,69-76 (2017).
  • Heller, D., Krestel, R., Ohler, U., Vingron, M., Marsico, A.: ssHMM: Extracting Intuitive Sequence-Structure Motifs from High-Throughput RNA-Binding Protein Data.Nucleic Acid Research.45,11004--11018 (2017).


  • Gruetze, T., Krestel, R., Naumann, F.: Topic Shifts in StackOverflow: Ask it like Socrates.Lecture Notes in Computer Science. p. 213--221. Springer (2016).
  • Grundke, M., Jasper, J., Perchyk, M., Sachse, J.P., Krestel, R., Neves, M.: TextAI: Enhancing TextAE with Intelligent Annotation Support.Proceedings of the 7th International Symposium on Semantic Mining in Biomedicine (SMBM 2016). pp. 80-84. CEUR-WS.org (2016).
  • Godde, C., Lazaridou, K., Krestel, R.: Classification of German Newspaper Comments.Proceedings of the Conference Lernen, Wissen, Daten, Analysen. pp. 299-310. CEUR-WS.org (2016).
  • Park, J., Blume-Kohout, M., Krestel, R., Nalisnick, E., Smyth, P.: Analyzing NIH Funding Patterns over Time with Statistical Text Analysis.Scholarly Big Data: AI Perspectives, Challenges, and Ideas (SBD 2016) Workshop at AAAI 2016. AAAI (2016).
  • Lazaridou, K., Krestel, R.: Identifying Political Bias in News Articles.International Conference on Theory and Practice of Digital Libraries. IEEE Technical Committee on Digital Libraries (2016).
  • Krestel, R., Mottin, D., Müller, E. eds: Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", Potsdam, Germany, September 12-14, 2016.CEUR-WS.org (2016).
  • Naumann, F., Krestel, R.: The Information Systems Group at HPI.SIGMOD Record. (2016).
  • Jenders, M., Krestel, R., Naumann, F.: Which Answer is Best? Predicting Accepted Answers in MOOC Forums.Proceedings of the 25th International Conference Companion on World Wide Web. pp. 679-684. International World Wide Web Conferences Steering Committee (2016).


  • Roick, M., Jenders, M., Krestel, R.: How to Stay Up-to-date on Twitter with General Keywords.Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. CEUR-WS.org (2015).
  • Gruetze, T., Yao, G., Krestel, R.: Learning Temporal Tagging Behaviour.Proceedings of the 24th International Conference on World Wide Web Companion (WWW). p. 1333--1338. ACM (2015).
  • Krestel, R., Werkmeister, T., Wiradarma, T.P., Kasneci, G.: Tweet-Recommender: Finding Relevant Tweets for News Articles.Proceedings of the 24th International World Wide Web Conference (WWW). ACM (2015).
  • Schubotz, T., Krestel, R.: Online Temporal Summarization of News Events.Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). pp. 679-684. IEEE Computer Society (2015).
  • Jenders, M., Lindhauer, T., Kasneci, G., Krestel, R., Naumann, F.: A Serendipity Model For News Recommendation.KI 2015: Advances in Artificial Intelligence - 38th Annual German Conference on AI, Dresden, Germany, September 21-25, 2015, Proceedings. pp. 111-123. Springer (2015).
  • Krestel, R., Dokoohaki, N.: Diversifying Customer Review Rankings.Neural Networks.66,36-45 (2015).


  • Krestel, R., Bergler, S., Witte, R.: Modeling human newspaper readers: The Fuzzy Believer approach.Natural Language Engineering.20,261--288 (2014).