Institut

Studium

Forschung


 

Martin Riedl

Dr.
Martin Riedl

Martin Riedl
Telefon +49 711 685-81408
Raum01.010
E-Mail
Anschrift
Universität Stuttgart
Institut für Maschinelle Sprachverarbeitung
Pfaffenwaldring 5 b
70569 Stuttgart
Deutschland

Seit Oktober 2017 arbeite ich in der Gruppe für theoretische Computerlinguistik.


Forschung
  • unsupervised methods
  • distributional semantics
Publikationen

Journals und Monologe

  • 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
  • 2015 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

Konferenzen

  • 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
  • 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). 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), 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), Gothenburg, Sweden
  • 2016 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 Dis- tributional 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 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