Kernel methods for word sense disambiguation and acronym expansion

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2006, Pages 1879-1880

  Joshi, Mahesh ^a   Pedersen, Ted ^a   Maclin, Richard ^a   Pakhomov, Serguei ^b  

^a UNIVERSITY OF MINNESOTA DULUTH   (United States)

^b Mayo Clinic College of Medicine   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; DATA STRUCTURES; KNOWLEDGE ACQUISITION; SEMANTICS;

ONTOLOGIES; SENSE DISAMBIGUATION; SUPPORT VECTOR MACHINES (SVM);

LEARNING SYSTEMS;

EID: 33750736287     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. Basili, R.; Cammisa, M.; and Moschitti, A. 2005. Effective use of WordNet semantics via kernel-based learning. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005), 1-8.
2. Cristianini, N.; Shawe-Taylor, J.; and Lodhi, H. 2001. Latent semantic kernels. In Proceedings of 18th International Conference on Machine Learning (ICML'01), 66-73.
3. Fellbaum, C. 1998. Wordnet, an electronic lexical database. MIT Press.
4. Gliozzo, A.; Giuliano, C.; and Strapparava, C. 2005. Domain kernels for word sense disambiguation. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05), 403-410.
5. Joshi, M.; Pedersen, T.; and Maclin, R. 2005. A comparative study of support vector machines applied to the supervised word sense disambiguation problem in the medical domain. In Proceedings of the 2nd Indian International Conference on Artificial Intelligence (IICAI'05), 3449-3468.
6. Mihalcea, R., and Moldovan, D. 1999. An automatic method for generating sense tagged corpora. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI'99), 461-466.
7. Pakhomov, S.; Pedersen, T.; and Chute, C. 2005. Abbreviation and acronym disambiguation in clinical discourse. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA'05), 589-593.
8. Pakhomov, S. 2002. Semi-supervised maximum entropy based approach to acronym and abbreviation normalization in medical texts. In 40th Meeting of the Association for Computational Linguistics (ACL'02), 160-167.