Hasso-Plattner-Institut
Prof. Dr. Felix Naumann
  
 

Publications

2021

  • 1.
    Risch, J., Alder, N., Hewel, C., Krestel, R.: PatentMatch: A Dataset for Matching Patent Claims & Prior Art. Proceedings of the 2nd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech@SIGIR) (2021).
     
  • 2.
    Jain, N., Kalo, J.-C., Balke, W.-T., Krestel, R.: Do Embeddings Actually Capture Knowledge Graph Semantics?. Extended Semantic Web Conference (ESWC) 2021. pp. 143–159. Springer (2021).
     
  • 3.
    Repke, T., Krestel, R.: Robust Visualisation of Dynamic Text Collections: Measuring and Comparing Dimensionality Reduction Algorithms. ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR). pp. 1–4 (2021).
     
  • 4.
    Risch, J., Repke, T., Kohlmeyer, L., Krestel, R.: ComEx: Comment Exploration on Online News Platforms. Joint Proceedings of the ACM IUI 2021 Workshops co-located with the 26th ACM Conference on Intelligent User Interfaces (IUI). pp. 1–7. CEUR-WS.org (2021).
     
  • 5.
    Risch, J., Schmidt, P., Krestel, R.: Data Integration for Toxic Comment Classification: Making More Than 40 Datasets Easily Accessible in One Unified Format. Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH@ACL) (2021).
     
  • 6.
    Risch, J., Hager, P., Krestel, R.: Multifaceted Domain-Specific Document Embeddings. Proceedings of the 19th Annual Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)(NAACL). ACL (2021).
     
  • 7.
    Schwanhold, R., Repke, T., Krestel, R.: Modeling the Evolution of Word Senses with Force-Directed Layouts of Co-occurrence Networks. Proceedings of the 2nd International Workshop on Computational Approaches to Historical Language Change (LChange@ACL 2021). 1–6 (2021).
     
  • 8.
    Belaid, M.K., Rabus, M., Krestel, R.: CrashNet: an encoder–decoder architecture to predict crash test outcomes. Data Min Knowl Disc. (2021).
     
  • 9.
    Repke, T., Krestel, R.: Extraction and Representation of Financial Entities from Text. In: Consoli, S., Reforgiato Recupero, D., and Saisana, M. (eds.) Data Science for Economics and Finance. pp. 241–263. Springer, Cham (2021).
     

2020

  • 1.
    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).
     
  • 2.
    Jain, N., Bartz, C., Bredow, T., Metzenthin, E., Otholt, J., Krestel, R.: Semantic Analysis of Cultural Heritage Data: Aligning Paintings and Descriptions in Art-Historic Collections. International Workshop on Fine Art Pattern Extraction and Recognition in conjunction with the 25th International Conference on Pattern Recognition (ICPR 2020) (2020).
     
  • 3.
    Risch, J., Künstler, V., Krestel, R.: HyCoNN: Hybrid Cooperative Neural Networks for Personalized News Discussion Recommendation. Proceedings of the International Joint Conferences on Web Intelligence and Intelligent Agent Technologies (WI-IAT) (2020).
     
  • 4.
    Jain, N., Krestel, R.: Learning Fine-Grained Semantics for Multi-Relational Data. International Semantic Web Conference, 2020 Posters and Demos (2020).
     
  • 5.
    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). pp. 3117–3124. ACM (2020).
     
  • 6.
    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).
     
  • 7.
    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). pp. 1–12 (2020).
     
  • 8.
    Risch, J., Ruff, R., Krestel, R.: Explaining Offensive Language Detection. Journal for Language Technology and Computational Linguistics (JLCL). 34, 29–47 (2020).
     
  • 9.
    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).
     
  • 10.
    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).
     
  • 11.
    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).
     
  • 12.
    Risch, J., Garda, S., Krestel, R.: Hierarchical Document Classification as a Sequence Generation Task. Proceedings of the Joint Conference on Digital Libraries (JCDL). pp. 147–155 (2020).
     
  • 13.
    Jain, N.: Domain-Specific Knowledge Graph Construction for Semantic Analysis. Extended Semantic Web Conference (ESWC 2020) Ph.D. Symposium (2020).
     
  • 14.
    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).
     
  • 15.
    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).
     
  • 16.
    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).
     
  • 17.
    Repke, T., Krestel, R.: Exploration Interface for Jointly Visualised Text and Graph Data. International Conference on Intelligent User Interfaces Companion (IUI ’20). (2020).
     
  • 18.
    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).
     
  • 19.
    Risch, J., Alder, N., Hewel, C., Krestel, R.: PatentMatch: A Dataset for Matching Patent Claims with Prior Art. ArXiv e-prints 2012.13919. (2020).
     

2019

  • 1.
    Risch, J., Krestel, R.: Domain-specific word embeddings for patent classification. Data Technologies and Applications. 53, 108–122 (2019).
     
  • 2.
    Risch, J., Krestel, R.: Measuring and Facilitating Data Repeatability in Web Science. Datenbank-Spektrum. 19, 117–126 (2019).
     
  • 3.
    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). pp. 115–122. Springer (2019).
     
  • 4.
    Kellermeier, T., Repke, T., Krestel, R.: Mining Business Relationships from Stocks and News. MIDAS@ECML-PKDD. (2019).
     
  • 5.
    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). pp. 403–408. German Society for Computational Linguistics & Language Technology, Erlangen, Germany (2019).
     

2018

  • 1.
    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).
     
  • 2.
    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).
     
  • 3.
    Repke, T., Krestel, R.: Topic-aware Network Visualisation to Explore Large Email Corpora. International Workshop on Big Data Visual Exploration and Analytics (BigVis). (2018).
     
  • 4.
    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).
     
  • 5.
    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).
     
  • 6.
    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).
     
  • 7.
    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).
     
  • 8.
    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).
     
  • 9.
    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). pp. 1–4. ACM (2018).
     
  • 10.
    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).
     
  • 11.
    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).
     
  • 12.
    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).
     
  • 13.
    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).
     
  • 14.
    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).
     

2017

  • 1.
    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. pp. 12:1–12:2. ACM, New York, NY, USA (2017).
     
  • 2.
    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).
     
  • 3.
    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).
     
  • 4.
    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).
     
  • 5.
    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).
     
  • 6.
    Lazaridou, K., Krestel, R., Naumann, F.: Identifying Media Bias by Analyzing Reported Speech. International Conference on Data Mining. IEEE (2017).
     
  • 7.
    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).
     
  • 8.
    Naumann, F., Krestel, R.: Das Fachgebiet „Informationssysteme“ am Hasso-Plattner-Institut. Datenbankspektrum. 17, 69–76 (2017).
     

2016

  • 1.
    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).
     
  • 2.
    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).
     
  • 3.
    Gruetze, T., Krestel, R., Naumann, F.: Topic Shifts in StackOverflow: Ask it like Socrates. Lecture Notes in Computer Science. pp. 213–221. Springer (2016).
     
  • 4.
    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).
     
  • 5.
    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).
     
  • 6.
    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).
     
  • 7.
    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).
     
  • 8.
    Naumann, F., Krestel, R.: The Information Systems Group at HPI. SIGMOD Record. (2016).
     

2015

  • 1.
    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).
     
  • 2.
    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).
     
  • 3.
    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).
     
  • 4.
    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).
     
  • 5.
    Krestel, R., Dokoohaki, N.: Diversifying Customer Review Rankings. Neural Networks. 66, 36–45 (2015).
     
  • 6.
    Gruetze, T., Yao, G., Krestel, R.: Learning Temporal Tagging Behaviour. Proceedings of the 24th International Conference on World Wide Web Companion (WWW). pp. 1333–1338. ACM (2015).
     

2014

  • 1.
    Krestel, R., Bergler, S., Witte, R.: Modeling human newspaper readers: The Fuzzy Believer approach. Natural Language Engineering. 20, 261–288 (2014).