Lukas Michelbacher
Lukas Michelbacher, Ph.D. candidate
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Statistical Natural Language Processing Group Institute for Natural Language Processing (IMS) University of Stuttgart Pfaffenwaldring 5b 70569 Stuttgart Germany |
/fak5/ims/~michells |
Projects
- Collaborative Research Center (SFB) 732 (Project D7)
- WordGraph (funded by the German Research Foundation)
Publications
semantic head recognition (multi-word units, distributional semantics and non-compositionality)
- Lukas Michelbacher, Alok Kothari, Martin Forst, Christian Lioma and Hinrich Schütze (2011). A Cascaded Classification Approach to Semantic Head Recognition. EMNLP. pdf | bibtex
asymmetric association measures
- Lukas Michelbacher, Stefan Evert and Hinrich Schütze (2011). Asymmetry in Corpus-Derived and Human Word Associations. Corpus Linguistics and Linguistic Theory. pdf | bibtex | pre-publication pdf | web appendix
- Lukas Michelbacher, Stefan Evert and Hinrich Schütze (2007). Asymmetric Association Measures. RANLP. pdf | bibtex
graph-based NLP
- Florian Laws, Lukas Michelbacher, Beate Dorow, Christian Scheible, Ulrich Heid and Hinrich Schütze (2010). A Linguistically Grounded Graph Model for Bilingual Lexicon Extraction. COLING. pdf | bibtex
- Christian Scheible, Florian Laws, Lukas Michelbacher and Hinrich Schütze (2010). Sentiment Translation through Multi-Edge Graphs. COLING. pdf | bibtex
- Lukas Michelbacher, Florian Laws, Beate Dorow, Ulrich Heid and Hinrich Schütze (2010). Building a Cross-lingual Relatedness Thesaurus using a Graph Similarity Measure.
LREC. pdf and bibtex - Beate Dorow, Florian Laws, Lukas Michelbacher, Christian Scheible and Jason Utt (2009). A Graph-Theoretic Algorithm for Automatic Extension of Translation Lexicons.
In GEMS Workshop (EACL). pdf | bibtex
Professional Activities
- review: AAAI 2012,EACL 2012, IJCNLP 2011, GEMS Workshop 2011, LREC 2010, COLING 2010
Links
- Choose your career in linguistics
- How to write a scientific paper
- Choose your workflow apps (overview on how to get started with LaTeX, Emacs and R)
- The Ph.D. Grind: A must-read for Ph.D. students of CS and related fields

