A list of my publications can also be found on Google Scholar.

Selected Publications

• Martin Riedl and Chris Biemann (2018): Using Semantics for Granularities of Tokenization, Computational Linguistics, vol. 44, no. 3, p.483-524
• Martin Riedl, Sebastian Padó (2018): A Named Entity Recognition Shootout for German, In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Melbourne, Australia
• Seid Muhie Yimam, Sanja Štajner, Martin Riedl, Chris Biemann (2017): Complex Word Identification Task across Three Text Genres and Two User Groups. In Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan
• Sunny Mitra, Ritwik Mitra,Martin Riedl, Chris Biemann, Animesh Mukherjee and Pawan Goyal (2014): That’s sick dude!: Automatic identification of word sense change across different timescales. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), p. 1020-1029, Baltimore, MD, USA
• Chris Biemann, Martin Riedl (2013): Text: Now in 2D! A Framework for Lexical Expansion with Contextual Similarity. Journal of Language Modelling (JLM) 1(1), p.55-95
• Martin Riedl and Chris Biemann (2012): How Text Segmentation Algorithms Gain from Topic Models. In: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2012), p. 553-557, Montreal, Canada

Journals und Monologs

• Martin Riedl and Chris Biemann (2018): Using Semantics for Granularities of Tokenization, Computational Linguistics, vol. 44, no. 3, p.483-524
• Flavio Massimiliano Cecchini, Martin Riedl, Elisabetta Fersini, Chris Biemann (2018): A comparison of graph-based word sense induction clustering algorithms in a pseudoword evaluation framework, Language Resources and Evaluation (LRE), p. 1-38
• Martin Riedl (2016): Unsupervised Methods for Learning and Using Semantics of Natural Language, Dissertation, TU Darmstadt
• Sunny Mitra, Ritwik Mitra, Suman Kalyan Maity, Martin Riedl, Chris Biemann, Pawan Goyal and Animesh Mukherjee (2015): An automatic approach to identify word sense changes in text media across timescale, Natural Language Engineering (NLE), Special issue on Graph Methods for NLP, Vol. 21, p. 773-798
• Chris Biemann, Martin Riedl (2013): Text: Now in 2D! A Framework for Lexical Expansion with Contextual Similarity. Journal of Language Modelling (JLM) 1(1), p.55-95
• Martin Riedl and Chris Biemann (2012): Text Segmentation with Topic Models. Journal for Language Technology and Computational Linguistics (JLCL), vol. 27, no. 1, p. 47-70
• Martin Riedl (2010): Using protein identification data to improve mass spec- trometry feature extraction, Master Thesis, HS Mannheim
• Martin Riedl (2009): Usage of data mining to learn activity recognitions rules (in the field of ambient assisted living), Diploma Thesis, HS Mannheim
• Peter Findeisen, Diamandula Sismanidis, Martin Riedl, Victor Costina and Michael Neumaier (2005): Preanalytical impact of sample handling on pro- teome profiling experiments with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Clinical chemistry, 51(12):2409-11

Edited Volumes

• Dmitry Ustalov, Swapna Somasundaran, Peter Jansen, Goran Glavaš, Martin Riedl, Mihai Surdeanu, Michalis Vazirgiannis (Eds.) (2019): Proceedings of TextGraphs-13: Graph-based Methods for Natural Language Processing, Hong Kong, Association for Computational Linguistics
• Martin Riedl, Swapna Somasundaran, Goran Glavaš and Ed Hovy (Eds.) (2018): Proceedings of TextGraphs-12: Graph-based Methods for Natural Language Processing, San Diego, CA, USA, Association for Computational Linguistics
• Martin Riedl, Swapna Somasundaran, Goran Glavaš and Ed Hovy (Eds.) (2017): Proceedings of TextGraphs-11: Graph-based Methods for Natural Language Processing, Vancouver, Canada, Association for Computational Linguistics
• V.G.Vinod Vydiswaran, Martin Riedl, Tanmoy Chakraborty (Eds.) (2016): Proceedings of TextGraphs-10: Graph-based Methods for Natural Language Processing, San Diego, CA, USA, Association for Computational Linguistics

Conferences

• Martin Riedl, Sebastian Padó (2018): A Named Entity Recognition Shootout for German, In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Melbourne, Australia
• Ahmed Elsafty, Martin Riedl, Chris Biemann (2018): Document-based Recommender System for Job Postings using Dense Representations, In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies in the Industry Track (NAACL-HLT 2018). New Orleans, LO, USA
• Seid Muhie Yimam, Sanja Štajner, Martin Riedl, Chris Biemann (2017): Complex Word Identification Task across Three Text Genres and Two User Groups. In Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP), p. 401–407, Taipei, Taiwan
• Martin Riedl, Chris Biemann (2017): There’s no ‘Count or Predict’ but task-based selection for distributional models. In Proceedings of the 12th International Conference on Computational Semantics (IWCS). Montpellier, France
• Seid Muhie Yimam, Sanja Štajner, Martin Riedl, Chris Biemann (2017): Multilingual and Cross-Lingual Complex Word Identification. In Proceedings of The 2017 International Conference on Recent Advances in Natural Language Processing (RANLP), p. 813–822, Varna, Bulgaria
• Prasanth Kolachina, Martin Riedl, Chris Biemann (2017): Replacing OOV Words For Dependency Parsing With Distributional Semantics. Proceedings of the Nordic Conference on Computational Linguistics (NoDaLiDa 2017), p. 11-19, Gothenburg, Sweden
• Flavio M. Cecchini, Martin Riedl, Chris Biemann (2017): Using Pseudowords for Algorithm Comparison: An Evaluation Framework for Graph-based Word Sense Induction. Proceedings of the Nordic Conference on Computational Linguistics (NoDaLiDa 2017), p. 105-114, Gothenburg, Sweden
• Martin Riedl, Tim Feuerbach and Chris Biemann (2016): Running into Brick Walls Attempting to Improve a Simple Unsupervised Parser, In: Proceedings of the Conference on Natural Language Processing (KONVENS 2016), p. 215-220, Bochum, Germany
• Alexander Panchenko, Johannes Simon, Martin Riedl and Chris Biemann (2016): Noun Sense Induction and Disambiguation using Graph-Based Distri- butional Semantics, In: Proceedings of the Conference on Natural Language Processing (KONVENS 2016), p. 192-202, Bochum, Germany
• Martin Riedl and Chris Biemann (2016): Unsupervised Compound Splitting With Distributional Semantics Rivals Supervised Methods. In: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2016), p. 617-622, San Diego, CA, USA
• Martin Riedl and Chris Biemann (2015): A Single Word is not Enough: Ranking Multiword Expressions Using Distributional Semantics. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP 2015), p. 2430-2440, Lisboa, Portugal
• Tim Feuerbach, Martin Riedl and Chris Biemann (2015): Distributional Semantics for Resolving Bridging Mentions. In: Proceedings of the Conference on Recent Advances in Natural Language Processing (RANLP ’15), p. 192-199, Hissar, Bulgaria
• Eugen Ruppert, Jonas Klesy, Martin Riedl, Chris Biemann (2015): Rule- based Dependency Parse Collapsing and Propagation for German and English. In: Proceedings of the International Confernce of the German Society for Computational Linguistics and Language Technology (GSCL 2015), p. 58-66, Duisburg, Germany
• Eugen Ruppert, Manuel Kaufmann, Martin Riedl and Chris Biemann (2015): JOBIMVIZ: A Web-based Visualization for Graph-based Distributional Seman- tic Models. In: Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL) System Demonstrations, p. 103-108, Beijing, China
• Martin Riedl, Michael Glass and Alfio Gliozzo (2014): Lexical Substitution for the Medical Domain. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), p. 610-614, Doha, Qatar
• Martin Riedl, Irina Alles, Chris Biemann (2014), Combining Supervised and Unsupervised Parsing for Distributional Similarity. In: Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), p. 1435-1446, Dublin, Ireland
• Sunny Mitra, Ritwik Mitra,Martin Riedl, Chris Biemann, Animesh Mukherjee and Pawan Goyal (2014): That’s sick dude!: Automatic identification of word sense change across different timescales. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), p. 1020-1029, Baltimore, MD, USA
• Martin Riedl, Richard Steuer and Chris Biemann (2014): Distributed Distributional Similarities of Google Books over Centuries. In: Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC 2014), p. 1401-1405, Reykjavik, Iceland
• Martin Riedl and Chris Biemann (2013): Scaling to Large3 Data: An efficient and effective method to compute Distributional Thesauri. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), p. 884-890, Seattle, WA, USA
• Martin Riedl and Chris Biemann (2012): How Text Segmentation Algorithms Gain from Topic Models. In: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2012), p. 553-557, Montreal, Canada
• Martin Riedl and Chris Biemann (2012): TopicTiling: A Text Segmentation Algorithm based on LDA. In: Proceddings of the Student Research Workshop of the 50th Meeting of the Association for Computational Linguistics, p. 37-42, Jeju, South Korea

Workshops

• Martin Riedl, Daniela Betz, Sebastian Padó (2019): Clustering-Based Article Identification in Historical Newspapers, In Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature in conjunction with NAACL 2019, p. 12-17, Melbourne, Australia
• Martin Riedl and Chris Biemann (2016): Impact of MWE Resources on Multiword Recognition. In: Proceedings of the 12th Workshop on Multiword Expressions in conjunction with ACL 2016, p. 107-111, Berlin, Germany
• Seid Muhie Yimam and Héctor Martínez Alonso and Martin Riedl and Chris Biemann (2016): Learning Paraphrasing for Multiword Expressions. In: Pro- ceedings of the 12th Workshop on Multiword Expressions in conjunction with ACL 2016, p. 1-10, Berlin, Germany
• Alfio Gliozzo, Chris Biemann Chris, Martin Riedl, Bonaventura Coppola, Michael R. Glass and Matthew Hatem (2013): JoBimText Visualizer: A Graph- based Approach to Contextualizing Distributional Similarity. In: Proceedings of the 8th Workshop on TextGraphs held in conjunction with EMNLP 2013, p. 6-10, Seattle, WA, USA
• Chris Biemann and Martin Riedl (2013): From Global to Local Similarities: A Graph-Based Contextualization Method using Distributional Thesauri. In: Proceedings of the 8th Workshop on TextGraphs held in conjunction with EMNLP 2013, p. 39-43, Seattle, WA, USA
• Janneke Rauscher, Leonard Swiezinski, Martin Riedl and Chris Biemann (2013): Exploring Cities in Crime: Significant Concordance and Co-occurrence in Quantitative Literary Analysis. In: Proceedings of the Computational Linguistics for Literature Workshop held in conjunction with the NAACL HLT 2013, p.61-71, Atlanta, GA, USA
• Martin Riedl and Chris Biemann (2012): Sweeping through the Topic Space: Bad luck? Roll again!. In: Proceedings of the ROBUS-UNSUP 2012: Joint Workshop on Unsupervised and Semi-Supervised Learning in NLP held in conjunction with EACL 2012, p. 19-27, Avignon, France
• Holger Storf, Martin Becker and Martin Riedl (2009): Rule-based Activity Recognition Framework: Challenges, Technique and Learning. In: Proceedings of the 1st PervaSense Workshop held in conjunction with Pervasive Health 2009, p. 1-7, London, England