Segment-based hidden Markov models for Information Extraction

COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference

Volumn 1, Issue , 2006, Pages 481-488

  Gu, Zhenmei ^a   Cercone, Nick ^b  

^a UNIVERSITY OF WATERLOO   (Canada)

^b DALHOUSIE UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; INFORMATION RETRIEVAL; REDUNDANCY;

EXTRACTION PROCESS; HIDDEN MARKOV MODELS (HMMS); SEGMENT-BASED;

HIDDEN MARKOV MODELS;

EID: 84859038485     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1220175.1220236     Document Type: Conference Paper

References (11)

1. D. M. Bikel, S. Miller, R. Schwartz, and R. Weischedel. 1997. Nymble: a highperformance learning name-finder. In Proceedings of ANLP-97, pages 194-201.
2. D. Freitag and A. McCallum. 1999. Information extraction with HMMs and shrinkage. In Proceedings of the AAAI-99 Workshop on Machine Learning for Information Extraction.
3. W. Gale and G. Sampson. 1995. Good-turning smoothing without tears. Journal of Quantitative Linguistics, 2:217-37.
4. Z. Gu and N. Cercone. 2006. Naive bayes modeling with proper smoothing for information extraction. In Proceedings of the 2006 IEEE International Conference on Fuzzy Systems.
5. F. Jelinek and R. L. Mercer. 1980. Intepolated estimation of markov source parameters from sparse data. In E. S. Gelesma and L. N. Kanal, editors, Proceedings of the Wrokshop on Pattern Recognition in Practice, pages 381-397, Amsterdam, The Netherlands: North-Holland, May.
6. T. R. Leek. 1997. Information extraction using hidden markov models. Master's thesis, UC San Diego.
7. A. McCallum, D. Freitag, and F. Pereira. 2000. Maximum entropy Markov models for informaion extraction and segmentation. In Proceedings of ICML-2000.
8. Andrew McCallum. 2003. Efficiently inducing features of conditional random fields. In Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI03).
9. F. Peng and A. McCallum. 2004. Accurate information extraction from research papers using conditional random fields. In Proceedings of Human Language Technology Conference and North American Chapter of the Association for Computational Linguistics.
10. L. Peshkin and A. Pfeffer. 2003. Bayesian information extraction network. In Proceedings of the Eighteenth International Joint Conf. on Artificial Intelligence.
11. L. Rabiner. 1989. A tutorial on hidden Markov models and selected applications in speech recognition. In Proceedings of the IEEE, volume 77(2).