The use of classifiers in sequential inference

Advances in Neural Information Processing Systems

Volumn , Issue , 2001, Pages

  Punyakanok, Vasin ^a   Roth, Dan ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COHERENT INFERENCE; CONSTRAINT SATISFACTION; MARKOVIAN; OBSERVATION STRUCTURE; PHRASE STRUCTURE; SHALLOW PARSING;

MARKOV PROCESSES;

EID: 84899004090     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. S. P. Abney. Parsing by chunks. In S. P. A. R. C. Berwick and C. Tenny, editors, Principle-based parsing: Computation and Psycholinguistics, pages 257-278. Kluwer, Dordrecht, 1991.
2. D. Appelt, J. Hobbs, J. Bear, D. Israel, and M. Tyson. FASTUS: A finite-state processor for information extraction from real-world text. In Proc. of IJCAI, 1993.
3. S. Argamon, I. Dagan, and Y. Krymolowski. A memory-based approach to learning shallow natural language patterns. Journal of Experimental and Theoretical Artificial Intelligence, special issue on memory-based learning, 10:1-22, 1999.
4. C. Burge and S. Karlin. Finding the genes in genomic DNA. Current Opinion in Structural Biology, 8:346-354, 1998.
5. C. Cardie and D. Pierce. Error-driven pruning of treebanks grammars for base noun phrase identification. In Proceedings of ACL-98, pages 218-224, 1998.
6. A. Carlson, C. Cumby, J. Rosen, and D. Roth. The SNoW learning architecture. Technical Report UIUCDCS-R-99-2101, UIUC Computer Science Department, May 1999.
7. K. W. Church. A stochastic parts program and noun phrase parser for unrestricted text. In Proc. of ACL Conference on Applied Natural Language Processing, 1988.
8. J. W. Fickett. The gene identification problem: An overview for developers. Computers and Chemistry, 20:103-118, 1996.
9. D. Freitag and A. McCallum. Information extraction using HMMs and shrinkage. In Papers from the AAAI-99 Workshop on Machine Learning for Information Extraction, 31-36, 1999.
10. A. R. Golding and D. Roth. A Winnow based approach to context-sensitive spelling correction. Machine Learning, 34(1-3): 107-130, 1999.
11. G. Greffenstette. Evaluation techniques for automatic semantic extraction: comparing semantic and window based approaches. In ACL'93 workshop on the Acquisition of Lexical Knowledge from Text, 1993.
12. R. Grishman. The NYU system for MUC-6 or where's syntax? In B. Sundheim, editor, Proceedings of the Sixth Message Understanding Conference. Morgan Kaufmann Publishers, 1995.
13. D. Gusfield and L. Pitt. A bounded approximation for the minimum cost 2-SAT problems. Algorithmica, 8:103-117, 1992.
14. Z. S. Harris. Co-occurrence and transformation in linguistic structure. Language, 33(3):283-340, 1957.
15. D. Haussler. Computational genefinding. Trends in Biochemical Sciences, Supplementary Guide to Bioinformatics, pages 12-15, 1998.
16. R. Khardon and D. Roth. Learning to reason. J. ACM, 44(5):697-725, Sept. 1997.
17. A. Mackworth. Constraint Satisfaction. In S. C. Shapiro, editor, Encyclopedia of Artificial Intelligence, pages 285-293, 1992. Volume 1, second edition.
18. M. P. Marcus, B. Santorini, and M. Marcinkiewicz. Building a large annotated corpus of English: The Penn Treebank. Computational Linguistics, 19(2):313-330, June 1993.
19. A. McCallum, D. Freitag, and F. Pereira. Maximum entropy Markov models for information extraction and segmentation. In proceedings of ICML-2000, 2000. to appear.
20. N. Morgan and H. Bourlard. Continuous speech recognition. IEEE Signal Processing Magazine, 12(3):24-42, 1995.
21. M. Munoz, V. Punyakanok, D. Roth, and D. Zimak. A learning approach to shallow parsing. In EMNLP-VLC99, 1999.
22. L. R. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-285, 1989.
23. L. A. Ramshaw and M. P. Marcus. Text chunking using transformation-based learning. In Pwceedings of the Third Annual Workshop on Very Large Corpora, 1995.
24. D. Roth. Learning to resolve natural language ambiguities: A unified approach. In Proceedings of the National Conference on Artificial Intelligence, pages 806-813, 1998.
25. D. Roth, M.-H. Yang, and N. Ahuja. Learning to recognize objects. In CVPR'00, The IEEE Conference on Computer Vision and Pattern Recognition, pages 724-731, 2000.
26. L. G. Valiant. Projection learning. In Proceedings of the Conference on Computational Learning Theory, pages 287-293, 1998.