Coarse word-sense disambiguation using common sense

AAAI Fall Symposium - Technical Report

Volumn FS-10-02, Issue , 2010, Pages 46-51

  Havasi, Catherine ^a   Speer, Robert ^a   Pustejovsky, James ^b  

^a MIT MEDIA LAB   (United States)

^b BRANDEIS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BLENDING; ONTOLOGY;

COMMON SENSE; COMMONSENSE REASONING; CONCEPTNET; F-SCORE; REASONING TECHNIQUES; WORD MEANING; WORD SENSE; WORD SENSE DISAMBIGUATION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 79960149218     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Cai, J. F.; Lee, W.S.; and Teh, Y. W. 2007. Nus-ml: Improving word sense disambiguation using topic features. In Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval), 249-252. Prague, Czech Republic: Association for Computational Linguistics.
2. Chan, Y. S.; Ng, H. T.; and Zhong, Z. 2007. NUS-PT: Exploiting parallel texts for word sense disambiguation in the English all-words tasks. In Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval), 253-256. Prague, Czech Republic: Association for Computational Linguistics.
3. Chklovski, T., and Mihalcea, R. 2002. Building a sense tagged corpus with Open Mind Word Expert. In Proceedings of the ACL-02 workshop on Word sense disambiguation, 116-122. Morristown, NJ, USA: Association for Computational Linguistics.
4. Havasi, C.; Speer, R.; Pustejovsky, J.; and Lieberman, H. 2009. Digital intuition: Applying common sense using dimensionality reduction. IEEE Intelligent Systems.
5. Havasi, C.; Speer, R.; and Alonso, J. 2007. ConceptNet 3: a flexible, multilingual semantic network for common sense knowledge. In Recent Advances in Natural Language Processing.
6. Havasi, C.; Speer, R.; and Pustejovsky, J. 2009. Automatically suggesting semantic structure for a generative lexicon ontology. In Proceedings of the Generative Lexicon Conference.
7. Havasi, C. 2009. Discovering Semantic Relations Using Singular Value Decomposition Based Techniques. Ph.D. Dissertation, Brandeis University.
8. Navigli, R., and Litkowski, K. C. 2007. SemEval-2007: Task Summary. SemEval Web site. http://nlp.cs.swarthmore.edu/semeval/tasks/task07/summary. shtml.
9. Navigli, R.; Litkowski, K. C.; and Hargraves, O. 2007. SemEval-2007 task 07: Coarse-grained English all-words task. In Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval), 30-35. Prague, Czech Republic: Association for Computational Linguistics.
10. Navigli, R. 2006. Meaningful clustering of senses helps boost word sense disambiguation performance. In ACL-44: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics, 105-112. Morris-town, NJ, USA: Association for Computational Linguistics.
11. Novischi, A.; Srikanth, M.; and Bennett, A. 2007. LCC-WSD: System description for English coarse grained all words task at SemEval 2007. In Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval), 223-226. Prague, Czech Republic: Association for Computational Linguistics.
12. Snyder, B., and Palmer, M. 2004. The English all-words task. In Mihalcea, R., and Edmonds, P., eds., Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, 41-43. Barcelona, Spain: Association for Computational Linguistics.
13. Speer, R.; Havasi, C.; and Lieberman, H. 2008. AnalogySpace: Reducing the dimensionality of common sense knowledge. Proceedings of AAAI 2008.