Prof. Dr. Felix Naumann



  • Risch, J., Krestel, R.: Aggression Identification Using Deep Learning and Data Augmentation. Proceedings of the 27th International Conference on Computational Linguistics (COLING), 1st Workshop on Trolling, Aggression and Cyberbullying (2018).
  • Risch, J., Krestel, R.: Delete or not Delete? Semi-Automatic Comment Moderation for the Newsroom. Proceedings of the 27th International Conference on Computational Linguistics (COLING), 1st Workshop on Trolling, Aggression and Cyberbullying (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).
  • 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 2018). ACL, New Orleans, Louisiana, USA (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).
  • 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) (2018).
  • Repke, T., Krestel, R.: Topic-aware Network Visualisation to Explore Large Email Corpora. International Workshop on Big Data Visual Exploration and Analytics (BigVis). CEUR-WS.org (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).


  • 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).
  • 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).
  • Naumann, F., Krestel, R.: Das Fachgebiet „Informationssysteme“ am Hasso-Plattner-Institut. Datenbankspektrum. 17, 69-76 (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).
  • 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).
  • 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).
  • 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).


  • Gruetze, T., Krestel, R., Naumann, F.: Topic Shifts in StackOverflow: Ask it like Socrates. Lecture Notes in Computer Science. p. 213--221. Springer (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).
  • 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).
  • Naumann, F., Krestel, R.: The Information Systems Group at HPI. SIGMOD Record. (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).
  • 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).
  • 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).


  • 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).
  • 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).
  • 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).
  • Krestel, R., Dokoohaki, N.: Diversifying Customer Review Rankings. Neural Networks. 66, 36-45 (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., 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).


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