Machine learning approach to POS tagging

Machine Learning

Volumn 39, Issue 1, 2000, Pages 59-91

  Màrquez, Lluís ^a   Padró, Lluís ^a   Rodríguez, Horacio ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; DECISION THEORY; MATHEMATICAL MODELS; STATISTICAL METHODS; TREES (MATHEMATICS);

PART OF SPEECH (POS) TAGGING; STATISTICAL DECISION TREES;

LEARNING SYSTEMS;

EID: 17744401443     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1007673816718     Document Type: Article

References (72)

1. Aarts, E.H. & Korst, J.H. (1987). Boltzmann machines and their applications. In J.W. de Bakker, A.J. Nijman & P.C. Treleaven (Eds.). Proceedings PARLE (Parallel Architectures and Languages Europe). Lecture Notes in Computer Science, Vol. 258.
2. Bahl, L.R., Brown, P.E., DeSouza, P.V., & Mercer, R.L. (1989). A tree-based statistical language model for natural language speech recognition. IEEE Transactions on Acoustics, Speech and Signal Processing, 37(7), 1001-1008.
3. Baum, L.E. (1972). An inequality and associated maximization technique in statistical estimation for probabilistic functions of a Markov process. Inequalities, 3, 1-8.
4. Blum, A. & Mitchell, T. (1998). Combining labeled and unlabeled data with co-training. Proceedings of the 11th Annual Conference on Computational Learning Theory, COLT-98 (pp. 92-100). Madison, Wisconsin.
5. Breiman, L., Friedman, J.H., Olshen, R.A., & Stone, C.J. (1984). Classification and regression trees. The Wadsworth Statistics/Probability Series. Belmont, CA: Wadsworth International Group.
6. Brill, E. (1992). A simple rule-based part-of-speech tagger. Proceedings of the 3rd Conference on Applied Natural Language Processing, ANLP (pp. 152-155). ACL.
7. Brill, E. (1994). Some advances in rule-based part-of-speech tagging. Proceedings of the 12th National Conference on Artificial Intelligence, AAAI (pp. 722-727).
8. Brill, E. (1995). Unsupervised learning of disambiguation rules for part-of-speech tagging. Proceedings of the 3rd Workshop on Very Large Corpora (pp. 1-13). Massachusetts.
9. Brill, E. & Wu, J. (1998). Classifier combination for improved lexical disambiguation. Proceedings of the Joint 17th International Conference on Computational Linguistics and 36th Annual Meeting of the Association for Computational Linguistics, COLING-ACL (pp. 191-195). Montréal, Canada.
10. Cardie, C. (1994). Domain specific knowledge acquisition for conceptual sentence analysis. Ph.d. Thesis, University of Massachusets. Available as CMPSCI Technical Report 94-74, University of Massachusetts.
11. Carmona, J., Cervell, S., Màrquez, L., Martí, M., Padró, L., Placer, R., Rodríguez, H., Taulé, M., & Turmo, J. (1998). An environment for morphosyntactic processing of unrestricted spanish text. Proceedings of the 1st International Conference on Language Resources and Evaluation, LREC (pp. 915-922). Spain: Granada.
12. Chanod, J.-P. & Tapanainen, P. (1995). Tagging french - Comparing a statistical and a constraint-based method. Proceedings of the 7th Conference of the European Chapter of the Association for Computational Linguistics, EACL (pp. 149-156). Dublin, Ireland.
13. Church, K. W. (1988). A stochastic parts program and noun phrase parser for unrestricted text. Proceedings of the 1st Conference on Applied Natural Language Processing, ANLP (pp. 136-143). ACL.
14. Cover, T.M. & Thomas, J.A. (Eds.). (1991). Elements of information theory. John Wiley & Sons.
15. Cutting, D., Kupiec, J., Pedersen, J., & Sibun, P. (1992). A practical part-of-speech tagger. Proceedings of the 3rd Conference on Applied Natural Language Processing, ANLP (pp. 133-140). ACL.
16. Daelemans, W., Zavrel, J., Berck, P., & Gillis, S. (1996). MBT: A memory-based part-of-speech tagger generator. Proceedings of the 4th Workshop on Very Large Corpora (pp. 14-27). Copenhagen, Denmark.
17. DeRose, S.J. (1988). Grammatical category disambiguation by statistical optimization. Computational Linguistics, 14, 31-39.
18. Elworthy, D. (1993). Part-of-speech and phrasal tagging. Working Paper #10, ESPRIT BRA-7315 Acquilex II.
19. Elworthy, D. (1994). Does Baum-Welch re-estimation help taggers? Proceedings of the 4th Conference on Applied Natural Language Processing, ANLP (pp. 53-58). ACL.
20. Garside, R., Leech, G., & Sampson, G. (Eds.) (1987). The computational analysis of English: A corpus-based approach. London: Longman.
21. Greene, B.B. & Rubin, G.M. (1971). Automatic grammatical tagging of English. Technical Report, Department of Linguistics, Brown University.
22. Halteren, H.v., Zavrel, J., & Daelemans, W. (1998). Improving data driven wordclass tagging by system combination. Proceedings of the Joint 17th International Conference on Computational Linguistics and 36th Annual Meeting of the Association for Computational Linguistics, COLING-ACL (pp. 491-497). Montréal, Canada.
23. Karlsson, F., Voutilainen, A., Heikkilä, J., & Anttila, A. (Eds.). (1995). Constraint grammar: A language-independent system for parsing unrestricted text. Berlin: Mouton de Gruyter.
24. Kononenko, I., Simec, E., & Robnik-Sikonja, M. (1995). Overcoming the myopia of inductive learning algorithms with RELIEFF. Applied Intelligence, 10, 39-55.
25. Krenn, B. & Samuelsson, C. (1997). The linguists' guide to statistics: Don't panic. Technical Report Universität des Saarlandes. Postscript version of December 19, 1997 at URL: http://coli.uni-sb.de/˜christer.
26. Krovetz, R. (1997). Homonymy and polysemy in information retrieval. Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics. Joint ACL/EACL (pp. 72-79). Madrid, Spain.
27. Larrosa, J. & Meseguer, P. (1995a). An optimization-based heuristic for maximal constraint satisfaction. Proceedings of International Conference on Principles and Practice of Constraint Programming (pp. 103-120).
28. Larrosa, J. & Meseguer, P. (1995b). Constraint satisfaction as global optimization. Proceedings of 14th International Joint Conference on Artificial Intelligence, IJCAI '95 (pp. 579-584).
29. Lloyd, S.A. (1983). An optimization approach to relaxation labelling algorithms. Image and Vision Computing, 1(2), 85-91.
30. Lopez de Mántaras, R. (1991). A distance-based attribute selection measure for decision tree induction. Machine Learning, 6(1), 81-92.
31. Lopez de Mántaras, R., Cerquides, J., & Garcia, P. (1996). Comparing information-theoretic attribute selection measures: A statistical approach research report 96-16, IIIA. To appear in Artificial Intelligence Communications.
32. Magerman, D.M. (1996). Learning grammatical structure using statistical decision-trees. Proceedings of the 3rd International Colloquium on Grammatical Inference, ICGI (pp. 1-21). Springer-Verlag Lecture Notes Series in Artificial Intelligence 1147.
33. Marcus, M.P., Marcinkiewicz, M.A., & Santorini, B. (1993). Building a large annotated corpus of english: The penn treebank. Computational Linguistics, 19(2), pp. 313-330.
34. Màrquez, L. (1999). Part-of-speech tagging: A machine-learning approach based on decision trees. Ph.d. Thesis, Dep. Llenguatges i Sistemes Informàtics. Universitat Politècnica de Catalunya.
35. Màrquez, L. & Padró, L. (1997). A flexible POS tagger using an automatically acquired language model. Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics. Joint ACL/EACL (pp. 238-245). Madrid, Spain.
36. Màrquez, L., Padró, L., & Rodríguez, H. (1998). Improving tagging accuracy by voting taggers. Proceedings of the 2nd Conference on Natural Language Processing & Industrial Applications, NLP+IA/TAL+AI (pp. 149-155). New Brunswick, Canada.
37. Màrquez, L. & Rodríguez, H. (1995). Towards learning a constraint grammar from annotated corpora using decision trees. Working Paper #21, ESPRIT BRA-7315 Acquilex II.
38. Màrquez, L. & Rodríguez, H. (1997). Automatically acquiring a language model for POS tagging using decision trees. Proceedings of the Second Conference on Recent Advances in Natural Language Processing, RANLP (pp. 27-34). Tzigov Chark, Bulgaria.
39. Màrquez, L. & Rodríguez, H. (1998). Part-of-speech tagging using decision trees. Proceedings of the 10th European Conference on Machine Learning, ECML (pp. 25-36). Chemnitz, Germany. (Lecture Notes in Artificial Intelligence, Vol. 1398. Claire Nédellec and Céline Rouveirol Eds., Springer).
40. Màrquez, L. & Rodríguez, H. (1998). Part-of-speech tagging using decision trees. Proceedings of the 10th European Conference on Machine Learning, ECML (pp. 25-36). Chemnitz, Germany. (Lecture Notes in Artificial Intelligence, Vol. 1398. Claire Nédellec and Céline Rouveirol Eds., Springer).
41. McCarthy, J.F. & Lehnert, W.G. (1995). Using decision trees for coreference resolution. Proceedings of the 14th International Joint Conference on Artificial Intelligence, IJCAI (pp. 1050-1055).
42. Merialdo, B. (1994). Tagging english text with a probabilistic model. Computational Linguistics, 20(2), 155-171.
43. Mooney, R.J. (1996). Comparative experiments on disambiguating word senses: An illustration of the role of bias in machine learning. Proceedings of the 1st Conference on Empirical Methods in Natural Language Processing, EMNLP (pp. 82-91).
44. Nigam, K., McCallum, A., Thrun, S., & Mitchell, T. (1998). Learning to classify text from labeled and unlabeled documents. Proceedings of the 15th National Conference on Artificial Intelligence, AAAI-98 Madison, Wisconsin.
45. Oostdijk, N. (1991). Corpus linguistic and the automatic analysis of English. Amsterdam: Rodopi.
46. Padró, L. (1996). POS tagging using relaxation labelling. Proceedings of the 16th International Conference on Computational Linguistics, COLING (pp. 877-882). Copenhagen, Denmark.
47. Padró, L. (1998). A hybrid environment for syntax-semantic tagging. Ph.d. Thesis, Dep. Llenguatges i Sistemes Informàtics. Universitat Politècnica de Catalunya.
48. Padró, L. & Màrquez, L. (1998). On the evaluation and comparison of taggers: The effect of noise in testing corpora. Proceedings of the Joint 17th International Conference on Computational Linguistics and 36th Annual Meeting of the Association for Computational Linguistics, COLING-ACL (pp. 997-1002). Montréal, Canada.
49. Pelillo, M. & Maffione, A. (1994). Using simulated annealing to train relaxation labelling processes. Proceedings of ICANN '94 (pp. 250-253).
50. Pelillo, M. & Refice, M. (1994). Learning compatibility coefficients for relaxation labeling processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(9), 933-945.
51. Quinlan, J.R. (1993). C4.5: Programs for machine learning. San Mateo, CA: Morgan Kaufmann Publishers Inc.
52. Quinlan, J.R. (1986). Induction of decision trees. Machine Learning, 1, 81-106.
53. Ratnaparkhi, A. (1996). A maximum entropy part-of-speech tagger. Proceedings of the 1st Conference on Empirical Methods in Natural Language Processing, EMNLP.
54. Ratnaparkhi, A. (1997). A simple introduction to maximum entropy models for natural language processing. Technical Report 97-08, Institute for Research in Cognitive Science, University of Pennsylvania.
55. Richards, J., Landgrebe, D., & Swain, P. (1981). On the accuracy of pixel relaxation labelling. IEEE Transactions on Systems, Man and Cybernetics, 11(4), 303-309.
56. Ristad, E. & Thomas, R.G. (1996). Nonuniform Markov models. Proceedings of the International Conference on Acoustics, Speech and Signal Processing, Munich, Germany.
57. Ristad, E.S. (1997). Maximum entropy modeling for natural language. Joint ACL/EACL Tutorial Program, Madrid, Spain.
58. Rosenfeld, R. (1994). Adaptive statistical language modelling: A maximum entropy approach. Ph.d.Thesis, School of Computer Science, Carnegie Mellon University.
59. Rosenfeld, R., Hummel, R., & Zucker, S. (1976). Scene labelling by relaxation operations. IEEE Transactions on Systems, Man and Cybernetics, 6(6), 420-433.
60. Samuelsson, C., Tapanainen, P., & Voutilainen, A. (1996). Inducing constraint grammars. Proceedings of the 3rd International Colloquium on Grammatical Inference, ICGI (pp. 146-155). Montpellier, France.
61. Samuelsson, C. & Voutilainen, A. (1997). Comparing a linguistic and a stochastic tagger. Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (pp. 246-253). Madrid, Spain.
62. Saul, L. & Pereira, F. (1997). Aggregate and mixed-order Markov models for statistical language processing. Proceedings of the 2nd Conference on Empirical Methods in Natural Language Processing, EMNLP.
63. Schmid, H. (1994a). Part-of-speech tagging with neural networks. Proceedings of the 15th International Conference on Computational Linguistics, COLING (pp. 172-176). Kyoto, Japan.
64. Schmid, H. (1994b). Probabilistic part-of-speech tagging using decision trees. Proceedings of the Conference on New Methods in Language Processing (pp. 44-49). Manchester, UK.
65. Southwell, R. (1940). Relaxation methods in engineering science. Clarendon.
66. Torras, C. (1989). Relaxation and neural learning: Points of convergence and divergence. Journal of Parallel and Distributed Computing, 6, 217-244.
67. Voutilainen, A. (1994). Three studies of grammar-based surface parsing on unrestricted English text. Ph.d. Thesis, Department of General Linguistics. University of Helsinki.
68. Voutilainen, A. & Padró, L. (1997). Developing a hybrid NP parser. Proceedings of the 5th Conference on Applied Natural Language Processing, ANLP (pp. 80-97). Washington DC: ACL.
69. Waltz, D. (1975). Understanding line drawings of scenes with shadows: Psychology of Computer Vision. New York: McGraw-Hill.
70. Weischedel, R., Schwartz, R., Palmucci, J., Meteer, M., & Ramshaw, L. (1993). Coping with ambiguity and unknown words through probabilistic models. Computational Linguistics, 19(2), 359-382.
71. Wilks, Y. & Stevenson, M. (1997). Combining independent knowledge sources for word sense disambiguation. Proceedings of the Second Conference on Recent Advances in Natural Language Processing, RANLP (pp. 1-7), Tzigov Chark, Bulgaria.
72. Zhou, X. & Dillon, T.S. (1991). A statistical-heuristic feature selection criterion for decision tree induction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(8), 834-841.