Latent dirichlet allocation for tag recommendation R Krestel, P Fankhauser, W Nejdl Proceedings of the third ACM conference on Recommender systems, 61-68, 2009 | 697 | 2009 |
Challenges for toxic comment classification: An in-depth error analysis B van Aken, J Risch, R Krestel, A Löser Proceedings of the 2nd Workshop on Abusive Language Online (ALW) co-located …, 2018 | 274 | 2018 |
Explainable AI under contract and tort law: legal incentives and technical challenges P Hacker, R Krestel, S Grundmann, F Naumann Artificial Intelligence and Law 28, 415-439, 2020 | 128 | 2020 |
Aggression identification using deep learning and data augmentation J Risch, R Krestel Proceedings of the first workshop on trolling, aggression and cyberbullying …, 2018 | 97 | 2018 |
A Survey on Deep Learning for Patent Analysis R Krestel, R Chikkamath, C Hewel, J Risch World Patent Information 65, 102035, 2021 | 85 | 2021 |
Toxic comment detection in online discussions J Risch, R Krestel Deep learning-based approaches for sentiment analysis, 85-109, 2020 | 83 | 2020 |
Minding the source: Automatic tagging of reported speech in newspaper articles R Krestel, S Bergler, R Witte Proceedings of the International Language Resources and Evaluation …, 2008 | 83 | 2008 |
Personalized topic-based tag recommendation R Krestel, P Fankhauser Neurocomputing 76 (1), 61-70, 2012 | 77 | 2012 |
Bagging BERT models for robust aggression identification J Risch, R Krestel Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying …, 2020 | 75 | 2020 |
Domain-specific word embeddings for patent classification J Risch, R Krestel Data Technologies and Applications 53 (1), 108-122, 2019 | 70 | 2019 |
Do embeddings actually capture knowledge graph semantics? N Jain, JC Kalo, WT Balke, R Krestel The Semantic Web: 18th International Conference, ESWC 2021, Virtual Event …, 2021 | 62 | 2021 |
Tag recommendation using probabilistic topic models R Krestel, P Fankhauser ECML PKDD Discovery Challenge 2009, 131, 2009 | 54 | 2009 |
hpiDEDIS at GermEval 2019: Offensive Language Identification using a German BERT model. J Risch, A Stoll, M Ziegele, R Krestel KONVENS, 2019 | 53 | 2019 |
Why finding entities in Wikipedia is difficult, sometimes G Demartini, CS Firan, T Iofciu, R Krestel, W Nejdl Information Retrieval 13, 534-567, 2010 | 50 | 2010 |
Using co-occurrence of tags and resources to identify spammers R Krestel, L Chen Proceedings of 2008 ECML/PKDD Discovery Challenge Workshop, 38-46, 2008 | 48 | 2008 |
Identifying political bias in news articles K Lazaridou, R Krestel Bulletin of the IEEE TCDL 12 (2), 1-12, 2016 | 47 | 2016 |
Delete or not delete? Semi-automatic comment moderation for the newsroom J Risch, R Krestel Proceedings of the first workshop on trolling, aggression and cyberbullying …, 2018 | 41 | 2018 |
Offensive language detection explained J Risch, R Ruff, R Krestel Proceedings of the second workshop on trolling, aggression and cyberbullying …, 2020 | 40 | 2020 |
ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data D Heller, R Krestel, U Ohler, M Vingron, A Marsico Nucleic acids research 45 (19), 11004-11018, 2017 | 40 | 2017 |
Diversifying product review rankings: Getting the full picture R Krestel, N Dokoohaki 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and …, 2011 | 39 | 2011 |