| TopicTiling: a text segmentation algorithm based on LDA M Riedl, C Biemann Proceedings of ACL 2012 student research workshop, 37-42, 2012 | 222 | 2012 |
| Text: Now in 2D! a framework for lexical expansion with contextual similarity C Biemann, M Riedl Journal of Language Modelling 1 (1), 55-95, 2013 | 170 | 2013 |
| That's sick dude!: Automatic identification of word sense change across different timescales S Mitra, R Mitra, M Riedl, C Biemann, A Mukherjee, P Goyal arXiv preprint arXiv:1405.4392, 2014 | 124 | 2014 |
| Text segmentation with topic models M Riedl, C Biemann Journal for Language Technology and Computational Linguistics 27 (1), 47-69, 2012 | 89 | 2012 |
| An automatic approach to identify word sense changes in text media across timescales S Mitra, R Mitra, SK Maity, M Riedl, C Biemann, P Goyal, A Mukherjee Natural Language Engineering 21 (5), 773-798, 2015 | 88 | 2015 |
| Rule-based activity recognition framework: Challenges, technique and learning H Storf, M Riedl, M Becker Pervasive Computing Technologies for Healthcare, 2009. PervasiveHealth 2009 …, 2009 | 70 | 2009 |
| Preanalytical impact of sample handling on proteome profiling experiments with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry P Findeisen, D Sismanidis, M Riedl, V Costina, M Neumaier Clinical chemistry 51 (12), 2409-2411, 2005 | 62 | 2005 |
| CWIG3G2-complex word identification task across three text genres and two user groups SM Yimam, S Štajner, M Riedl, C Biemann Proceedings of the Eighth International Joint Conference on Natural Language …, 2017 | 58 | 2017 |
| A named entity recognition shootout for German M Riedl, S Padó Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 55 | 2018 |
| Multilingual and Cross-Lingual Complex Word Identification. SM Yimam, S Stajner, M Riedl, C Biemann RANLP, 813-822, 2017 | 49 | 2017 |
| How text segmentation algorithms gain from topic models M Riedl, C Biemann Proceedings of the 2012 Conference of the North American Chapter of the …, 2012 | 40 | 2012 |
| Unsupervised compound splitting with distributional semantics rivals supervised methods M Riedl, C Biemann Proceedings of the 2016 Conference of the North American Chapter of the …, 2016 | 34 | 2016 |
| Scaling to Large³ Data: An Efficient and Effective Method to Compute Distributional Thesauri M Riedl, C Biemann Proceedings of the 2013 Conference on Empirical Methods in Natural Language …, 2013 | 34 | 2013 |
| A single word is not enough: Ranking multiword expressions using distributional semantics M Riedl, C Biemann Proceedings of the 2015 conference on empirical methods in natural language …, 2015 | 27 | 2015 |
| Document-based recommender system for job postings using dense representations A Elsafty, M Riedl, C Biemann Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 25 | 2018 |
| Impact of MWE resources on multiword recognition M Riedl, C Biemann Proceedings of the 12th workshop on multiword expressions, 107-111, 2016 | 22 | 2016 |
| JoBimViz: a web-based visualization for graph-based distributional semantic models E Ruppert, M Kaufmann, M Riedl, C Biemann Proceedings of ACL-IJCNLP 2015 System Demonstrations, 103-108, 2015 | 21 | 2015 |
| Rule-based Dependency Parse Collapsing and Propagation for German and English. E Ruppert, J Klesy, M Riedl, C Biemann GSCL, 58-66, 2015 | 20 | 2015 |
| Unsupervised methods for learning and using semantics of natural language M Riedl Technische Universität Darmstadt, 2016 | 16 | 2016 |
| JoBimText visualizer: a graph-based approach to contextualizing distributional similarity C Biemann, B Coppola, M Glass, A Gliozzo, M Hatem, M Riedl Proceedings of TextGraphs-8 Graph-based Methods for Natural Language …, 2013 | 16 | 2013 |
Chris BiemannProfessor for Language Technology, University of Hamburginformatik.uni-hamburg.de의 이메일 확인됨