Personal Information

Name
Martin Riedl 
Position
Postdoctoral Researcher 
E-Mail
riedl(a-t)cs.tu-darmstadt.de 
Phone
+49 (6151) 16-23208
Fax
+49 (6151) 16-25412
Office
S2|02 A322
Address

TU Darmstadt - FB 20 
Hochschulstraße 10 
64289 Darmstadt
Germany

Professional Activities

Software

    • DRUID: A method for extracting MWE
    • JoBimText: A framework for distributional semantics
    • LexSub: A framework for lexical substitution
    • SECOS: An unsupervised method for splitting compounds
    • TopicTiling: A Text Segmentation Algorithm based on TextTiling using LDA

     

    Contributions:

    • cleartk-ml-crfsuite: A wrapper of Naoaki Okazaki's Conditional Random Fields (CRF) implementation CRFsuite for the UIMA based machine learning framework ClearTk.  The sourcecode and the Maven module are contributed to ClearTk.
    • dkpro-big-data: A framework that enables the easy execution of UIMA pipelines on a Hadoop cluster

    Organization of Events:

    • TextGraphs-10: Graph-based Methods for Natural Language Processing
      Workshop at NAACL-HLT 2016, San Diego, CA, June 17, 2016

    Scientific Committe:

    Publications

    Monographs

    • Martin Riedl (2016): Unsupervised Methods for Learning and Using Semantics of Natural Language, PhD Thesis, Technische Universität Darmstadt (pdf)
    • Martin Riedl (2010): Using protein identification data to improve mass spectrometry feature extraction, Master Thesis, Hochschule Mannheim
    • Martin Riedl (2009): Usage of data mining to learn activity recognition rules, Diploma Thesis (FH), Hochschule Mannheim

    Journal publications

    • Mitra, S., Mitra, R., Maity, S., Riedl, M., Biemann, C., Goyal, P., Mukherjee, A., (2015): An automatic approach to identify word sense changes in text media across timescale,  Natural Language Engineering, Special issue on Graph Methods for NLP, DOI: http://dx.doi.org/10.1017/S135132491500011X, 26 pages. Published online: 16 April 2015
    • Biemann, C., Riedl, M. (2013): Text: Now in 2D! A Framework for  Lexical Expansion with Contextual Similarity. Journal of Language Modelling 1(1):55--95 (pdf)
    • Riedl, M., Biemann, C. (2012): Text Segmentation with Topic Models. Journal for Language Technology and Computational Linguistics (JLCL), Vol. 27, No. 1, pp. 47--70, August 2012 (pdf)
    • Peter Findeisen, Diamandula Sismanidis, Martin Riedl, Victor Costina, Michael Neumaier (2005): Preanalytical impact of sample handling on proteome profiling experiments with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Clinical chemistry, Vol. 51, No. 12, pp. 2409--2411 (pdf)

    Conference proceedings

    • Martin Riedl, Tim Feuerbach, 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), Bochum, Germany (undefinedpdf)
    • Alexander Panchenko, Johannes Simon, Martin Riedl, Chris Biemann (2016):  Noun Sense Induction and Disambiguation using Graph-Based Distributional Semantics. In Proceedings of the 13th Conference on Natural Language Processing (KONVENS). Bochum, Germany (pdf)
    • Martin Riedl, 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), San Diego, CA, USA, (pdf,software,undefinedslides,video)
    • Martin Riedl, 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). Lisboa, Portugal (pdf,software)
    • Tim Feuerbach, Martin Riedl, Chris Biemann (2015): Distributional Semantics for Resolving Bridging Mentions. In: Proceedings of the Conference on Recent Advances in Natural Language Processing (RANLP '15), Hissar, Bulgaria (pdf,undefinedslides,source contribution,source bansal klein)
    • Eugen Ruppert, Jonas Klesy, Martin Riedl, Chris Biemann (2015): Rule-based Dependency Parse Collapsing and Propagation for German and English. In: Proceedings of the GSCL 2015. Duisburg, Germany (pdf)
    • Eugen Ruppert, Manuel Kaufmann, Martin Riedl, Chris Biemann (2015): JOBIMVIZ: A Web-based Visualization for Graph-based Distributional Semantic Models. In the Annual Meeting of the Association for Computational Linguistics (ACL) System Demonstrations, Beijing, China (pdf)
    • Martin Riedl, Michael Glass and Alfio Gliozzo (2014), Lexical Substitution for the Medical Domain. In Proceedings of EMNLP 2014. Doha, Qatar (pdf)
    • Martin Riedl, Irina Alles, Chris Biemann (2014), Combining Supervised and Unsupervised Parsing for Distributional Similarity. In Proceedings of COLING 2014. Dublin, Ireland (pdf,slides)
    • Mitra, S., Mitra, R., Riedl, M., Biemann, C., Mukherjee, A., Goyal, P. (2014) That’s sick dude!: Automatic identification of word sense change across different timescales. Proceedings of ACL 2014, Baltimore, MD, USA (pdf)
    • Riedl M., Steuer R., Biemann C. (2014): Distributed Distributional Similarities of Google Books over Centuries. Proceedings Fourth International Conference on Language Resources and Evaluation (LREC 2014), Reykjavik, Iceland. (pdf, resources)
    • Riedl M., Biemann C. (2013): Scaling to Large^3 Data: An efficient and effective method to compute Distributional Thesauri. Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013 (pdf)
    • Riedl M., Biemann C. (2012): How Text Segmentation Algorithms Gain from Topic Models, Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2012), Montreal, Canada. (pdf)
       

    Workshop proceedings

      • Riedl M., Biemann C. (2016): Impact of MWE Resources on Multiword Recognition, In: Proceedings of the 12th Workshop on Multiword Expressions in conjunction with ACL, 2016, Berlin, Germany (pdf,undefinedslides).
      • Yimam, S. H. and Alonso, H. A. and Riedl, M. and Biemann, C. (2016): Learning to Rank Paragraphese for MWE, In: Proceedings of the 12th Workshop on Multiword Expressions in conjunction with ACL, 2016, pages 107-111, Berlin, Germany (undefinedpdf)
      • Gliozzo A., Biemann C, Riedl M., Coppola B., Glass M. R., Hatem M. (2013): JoBimText Visualizer: A Graph-based Approach to Contextualizing Distributional Similarity. In: Proceedings of the 8th Workshop on TextGraphs in conjunction with EMNLP 2013 (pdf)
      • Biemann C., Riedl M (2013): From Global to Local Similarities: A Graph-Based Contextualization Method using Distributional Thesauri. Proceedings of the 8th Workshop on TextGraphs in conjunction with EMNLP 2013 (pdf)
      • Janneke Rauscher, Leonhard Swiezinski, Martin Riedl and Chris Biemann (2013): Exploring Cities in Crime: Significant Concordance and Co-occurrence in Quantitative Literary Analysis. Proceedings of the Computational Linguistics for Literature Workshop at NAACL-HLT 2013, Atlanta, GA, USA (pdf)
      • Riedl M., Biemann C. (2012): TopicTiling: A Text Segmentation Algorithm based on LDA, Proceedings of the Student Research Workshop of the 50th Meeting of the Association for Computational Linguistics, Jeju, Republic of Korea. (pdf)
      • Riedl M., Biemann C. (2012): Sweeping through the Topic Space: Bad luck? Roll again! In Proceedings of the Joint Workshop on Unsupervised and Semi-Supervised Learning in NLP held in conjunction with EACL 2012, Avignon, France (pdf)
      • Holger Storf, Martin Riedl, Martin Becker (2009): Rule-based activity recognition framework: Challenges, technique and learning. 3rd International Conference on Pervasive Computing Technologies for Healthcare at PervasiveHealth, London, England (pdf)

      Personal Interests

      music (trumpet & piano), motor bike riding, brewing beer, climbing, jogging

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