Learning Rules and Their Exceptions

Journal of Machine Learning Research

Volumn 2, Issue 4, 2002, Pages 669-693

  Déjean, Hervé ^a  

^a XEROX RESEARCH CENTRE EUROPE   (France)

Author keywords

Chunking; Learning Exceptions; Natural Language Processing; Rule Induction; Symbolic Learning

Indexed keywords

EID: 0346975926     PISSN: 15324435     EISSN: None     Source Type: Journal    
DOI: 10.1162/153244302320884588     Document Type: Article

References (31)

1. Steven Abney. Parsing via finite-state cascades. In Proceedings of the ESSLLI'96 Robust Parsing Workshop, 1996.
2. Aït-Mokhtar, Jean-Pierre Chanod, and Claude Roux. A multi-input dependency parser. In Seventh International Workshop on Parsing Technologies, Beijing, 2001.
3. Kamal M. Ali and Michael J. Pazzani. Reducing the small disjuncts problem by learning probabilistic concept descriptions. In Computational Learning Theory and Natural Learning Systems, volume III: Selecting Good Models, pages 183-199. MIT Press, 1995.
4. Shlomo Argamon, Ido Dagan, and Yuval Krymolowski. A memory-based approach to learning shallow natural language patterns. In COLING'98, Montréal, 1998.
5. Eric Brill. Transformation-based error-driven learning and natural language processing: A case study in part-of-speech tagging. Computational Linguistics, 21(4):543-565, 1995.
6. C.A. Brunk and M.J. Pazzani. An investigation of noise-tolerant relational concept learning algorithms. In L. Birnbaum and G. Collins, editors, Proceedings of the 8th International Workshop on Machine Learning, pages 389-393. Morgan Kaufmann, 1991.
7. Claire Cardie. Integrating case-based learning and cognitive biases for machine learning of natural language. Journal of Experimental Theoretical Artificial Intelligence, 11(3): 297-337, 1999.
8. Walter Daelemans, Antal van den Bosch, and Jakub Zavrel. Forgetting exceptions is harmful in language learning. Machine Learning, 34(1-3): 11-41, 1999.
9. Hervé Déjean. Using ALLiS for clausing. In Walter Daelemans and Rémi Zajac, editors, Proceedings of CoNLL-2001, pages 64-66. Toulouse, France, 2001.
10. Claire Grover, Andrei Mikheev, and Colin Matheson. LT TTT version 1.0: Text Tokenisation Software, 1999. http://www.ltg.ed.ac.uk/software/ttt/.
11. L. Holder. Unifying empirical and explanation-based learning by modeling the utility of learned knowledge. In Proceedings of the ML92 Workshop on Compilation and Speedup Learning, 1992.
12. Robert Holte, Liane Acker, and Bruce Porter. Concept learning and the problem of small disjuncts. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, 1989.
13. Lauri Karttunen, Tamás Gaál, and André Kempe. Xerox finite-state tool. Technical report, Xerox Research Centre, Grenoble, 1997.
14. Rob Koeling. Chunking with maximum entropy models. In Claire Cardie, Walter Daelemans, Claire Nedellec, and Erik Tjong Kim Sang, editors, Proceedings of CoNLL-2000 and LLL-2000, pages 139-141. Lisbon, Portugal, 2000.
15. Taku Kudoh and Yuji Matsumoto. Use of support vector learning for chunk identification. In Claire Cardie, Walter Daelemans, Claire Nedellec, and Erik Tjong Kim Sang, editors, Proceedings of CoNLL-2000 and LLL-2000, pages 142-144. Lisbon, Portugal, 2000.
16. M. P. Marcus, B. Santorini, and M. Marcinkiewicz. Building a large annotated corpus of english: The penn treebank. Computational Linguistics, 19(2):313-330, 1993.
17. Tom Mitchell. Machine Learning. McGraw Hill, 1997.
18. Raymond J. Mooney and Mary Elaine Califf. Induction of first-order decision lists: Results on learning the past tense of english verbs. Journal of Artificial Intelligence Research, 3: 1-24, 1995.
19. John Nerbonne, Anja Belz, Nicola Cancedda, Hervé Déjean, James Hammerton, Rob Koeling, Stasinos Konstantopoulos, Miles Osborne, Franck Thollard, and Erik F. Tjong Kim Sang. Learning computational grammars. In Walter Daelemans and Rémi Zajac, editors, Proceedings of CoNLL-2001, pages 97-104. Toulouse, France, 2001.
20. Michael Pazzani and Dennis Kibler. The role of prior knowledge in inductive learning. Machine Learning, 9:54-97, 1992.
21. F. Provost and V. Kolluri. A survey of methods for scaling up inductive learning algorithms. In Third International Conference on Knowledge Discovery and Data Mining, 1997.
22. J. R. Quinlan. The effect of noise on concept learning. In J. G. Carbonell and T. M. Mitchell, editors, Machine learning: An artificial intelligence approach, volume 2. Morgan Kaufmann:San Mateo CA, 1986.
23. J. R. Quinlan. Learning logical definitions from relations. Machine Learning, 5:239-266, 1990.
24. Lance A. Ramshaw and Mitchell P. Marcus. Text chunking using tranformation-based learning. In ACL Third Workshop on Very Large Corpora, pages 82-94, 1995.
25. Erik F. Tjong Kim Sang. Introduction to the CoNLL-2000 shared task: Chunking. In Claire Cardie, Walter Daelemans, Claire Nedellec, and Erik Tjong Kim Sang, editors, Proceedings of workshop on Computational Natural Language Learning, CoNLL-2000 and LLL-2000, pages 127-132. Lisbon, Portugal, 2000a.
26. Erik F. Tjong Kim Sang. Text chunking by system combination. In Claire Cardie, Walter Daelemans, Claire Nedellec, and Erik Tjong Kim Sang, editors, Proceedings of CoNLL 2000 and LLL-2000, pages 151-153. Lisbon, Portugal, 2000b.
27. Khalil Sima'an. Explanation-based learning of data oriented parsing. In Computational Natural Language Learning (CoNLL), ACL/EACL-97, Madrid, 1997.
28. Stephen Soderland. Learning information extraction rules for semi-structured and free text. Machine Learning, 34(1-3):233-272, 1999.
29. Hans van Halteren. Chunking with WPDV models. In Claire Cardie, Walter Daelemans, Claire Nedellec, and Erik Tjong Kim Sang, editors, Proceedings of CoNLL-2000 and LLL-2000, pages 154-156. Lisbon, Portugal, 2000.
30. C.J. van Rijsbergen. Information Retrieval. Buttersworth, 1979.
31. G. Webb and N. Brkic. Learning decision lists by prepending inferred rules. In Proceedings of the Australian Workshop on Machine Learning and Hybrid Systems, 1993.