Combining Sample Selection and Error-Driven Pruning for Machine Learning of Coreference Rules

Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing, EMNLP 2002

Volumn , Issue , 2002, Pages 55-62

  Ng, Vincent ^a   Cardie, Claire ^a  

^a Department of Computer Science and School of Operations Research and Information Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; NATURAL LANGUAGE PROCESSING SYSTEMS;

CLASSIFICATION RULES; CLASSIFICATION TASKS; COREFERENCE; COREFERENCE RESOLUTION; MACHINE-LEARNING; NOUN PHRASE; POTENTIAL PROBLEMS; SAMPLE ERROR; SAMPLES SELECTION; SKEWED CLASS DISTRIBUTIONS;

MACHINE LEARNING;

EID: 85037152226     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. C. Aone and S. W. Bennett. 1995. Evaluating Automated and Manual Acquisition of Anaphora Resolution Strategies. In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics, pages 122–129.
2. A. Blum and P. Langley. 1997. Selection of relevant features and examples in machine learning. Artificial Intelligence, pages 245–271.
3. C. Cardie and N. Howe. 1997. Improving minority class prediction using case-specific feature weights. In Proceedings of the Fourteenth International Conference on Machine Learning, pages 57–65.
4. C. Cardie and K. Wagstaff. 1999. Noun Phrase Coreference as Clustering. In Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-99), pages 82–89.
5. W. Cohen. 1995. Fast Effective Rule Induction. In Proceedings of the Twelfth International Conference on Machine Learning, San Francisco, CA.
6. A. Dempster. 1968. A generalization of Bayesian inference. Journal of the Royal Statistical Society, 30:205–247.
7. T. Fawcett. 1996. Learning with skewed class distributions — summary of responses. Machine Learning List: Vol. 8, No. 20.
8. D. F. Gordon and D. Perlis. 1989. Explicitly biased generalization. Computational Intelligence, 5:67–81.
9. S. Harabagiu, R. Bunescu, and S. Maiorano. 2001. Text and Knowledge Mining for Coreference Resolution. In Proceedings of the Second Meeting of the North America Chapter of the Association for Computational Linguistics (NAACL-2001), pages 55–62.
10. A. Kehler. 1997. Probabilistic Coreference in Information Extraction. In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, pages 163–173.
11. M. Kubat and S. Matwin. 1997. Addressing the Curse of Imbalanced Training Sets: One-Sided Selection. In Proceedings of the 14th International Conference on Machine Learning (ICML-97), pages 179–186.
12. J. McCarthy and W. Lehnert. 1995. Using Decision Trees for Coreference Resolution. In Proceedings of the Fourteenth International Conference on Artificial Intelligence, pages 1050–1055.
13. MUC-6. 1995. Proceedings of the Sixth Message Understanding Conference (MUC-6). Morgan Kaufmann, San Francisco, CA.
14. MUC-7. 1998. Proceedings of the Seventh Message Understanding Conference (MUC-7). Morgan Kaufmann, San Francisco, CA.
15. V. Ng and C. Cardie. 2002. Improving machine learning approaches to coreference resolution. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics.
16. M. Pazzani, C. Merz, P. Murphy, K. Ali, T. Hume, and C. Brunk. 1994. Reducing Misclassification Costs. In Proceedings of the Eleventh International Conference on Machine Learning, pages 217–225.
17. W. M. Soon, H. T. Ng, and D. C. Y. Lim. 2001. A Machine Learning Approach to Coreference Resolution of Noun Phrases. Computational Linguistics, 27(4):521–544.
18. M. Vilain, J. Burger, J. Aberdeen, D. Connolly, and L. Hirschman. 1995. A model-theoretic coreference scoring scheme. In Proceedings of the Sixth Message Understanding Conference (MUC-6), pages 45–52. Morgan Kaufmann.