Discriminative classifiers for deterministic dependency parsing

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

Volumn , Issue , 2006, Pages 316-323

  Hall, Johan ^a   Nivre, Joakim ^a,b   Nilsson, Jens ^a  

^a LINNAEUS UNIVERSITY   (Sweden)

^b UPPSALA UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS;

COMPLEX MODEL; DATA DRIVEN; DEPENDENCY PARSING; DETERMINISTIC PARSING; DETERMINISTICS; DISCRIMINATIVE CLASSIFIERS; FEATURE MODELS; SIMPLE++; SUPPORT VECTORS MACHINE; TREEBANKS;

SUPPORT VECTOR MACHINES;

EID: 85119998478     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (32)

1. Ezra Black, Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, and Salim Roukos. 1992. Towards history-based grammars: Using richer models for probabilistic parsing. In Proceedings of the 5th DARPA Speech and Natural Language Workshop, pages 31-37.
2. Chih-Chung Chang and Chih-Jen Lin. 2005. LIBSVM: A library for support vector machines.
3. Eugene Charniak and Mark Johnson. 2005. Coarse-to-fine n-best parsing and MaxEnt discriminative reranking. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 173-180.
4. Eugene Charniak. 2000. A Maximum-Entropy-Inspired Parser. In Proceedings of the First Annual Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL), pages 132-139.
5. Yuchang Cheng, Masayuki Asahara, and Yuji Matsumoto. 2005a. Chinese deterministic dependency analyzer: Examining effects of global features and root node finder. In Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing, pages 17-24.
6. Yuchang Cheng, Masayuki Asahara, and Yuji Matsumoto. 2005b. Machine learning-based dependency analyzer for Chinese. In Proceedings of the International Conference on Chinese Computing (ICCC).
7. Michael Collins and Nigel Duffy. 2005. Discriminative reranking for natural language parsing. Computational Linguistics, 31:25-70.
8. Michael Collins. 1997. Three generative, lexicalised models for statistical parsing. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL), pages 16-23.
9. Michael Collins. 1999. Head-Driven Statistical Models for Natural Language Parsing. Ph.D. thesis, University of Pennsylvania.
10. Walter Daelemans and Veronique Hoste. 2002. Evaluation of machine learning methods for natural language processing tasks. In Proceedings of the Third International Conference on Language Resources and Evaluation (LREC), pages 755-760.
11. Walter Daelemans and Antal Van den Bosch. 2005. Memory-Based Language Processing. Cambridge University Press.
12. Walter Daelemans, Veronique Hoste, Fien De Meulder, and Bart Naudts. 2003. Combined optimization of feature selection and algorithm parameter interaction in machine learning of language. In Proceedings of the 14th European Conference on Machine Learning (ECML), pages 84-95.
13. Jan Einarsson. 1976. Talbankens skriftspråkskonkordans. Lund University, Department of Scandinavian Languages.
14. Mark Johnson, Stuart Geman, Steven Canon, Zhiyi Chi, and Stefan Riezler. 1999. Estimators for stochastic “unification-based” grammars. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL), pages 535-541.
15. Taku Kudo and Yuji Matsumoto. 2001. Chunking with support vector machines. In Proceedings of the Second Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL).
16. Taku Kudo and Yuji Matsumoto. 2002. Japanese dependency analysis using cascaded chunking. In Proceedings of the Sixth Workshop on Computational Language Learning (CoNLL), pages 63-69.
17. David M. Magerman. 1995. Statistical decision-tree models for parsing. In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 276-283.
18. Mitchell P. Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz, Robert MacIntyre, Ann Bies, Mark Ferguson, Karen Katz, and Britta Schasberger. 1994. The Penn Treebank: Annotating predicate-argument structure. In Proceedings of the ARPA Human Language Technology Workshop, pages 114-119.
19. Ryan McDonald, Koby Crammer, and Fernando Pereira. 2005. Online large-margin training of dependency parsers. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 91-98.
20. Joakim Nivre and Mario Scholz. 2004. Deterministic dependency parsing of English text. In Proceedings of the 20th International Conference on Computational Linguistics (COLING), pages 64-70.
21. Joakim Nivre, Johan Hall, and Jens Nilsson. 2004. Memory-based dependency parsing. In Proceedings of the 8th Conference on Computational Natural Language Learning (CoNLL), pages 49-56.
22. Joakim Nivre. 2003. An efficient algorithm for projective dependency parsing. In Proceedings of the 8th International Workshop on Parsing Technologies (IWPT), pages 149-160.
23. Adwait Ratnaparkhi. 1997. A linear observed time statistical parser based on maximum entropy models. In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1-10.
24. Kenji Sagae and Alon Lavie. 2005. A classifier-based parser with linear run-time complexity. In Proceedings of the 9th International Workshop on Parsing Technologies (IWPT), pages 125-132.
25. Ben Taskar, Dan Klein, Michael Collins, Daphne Koller, and Christopher Manning. 2004. Max-margin parsing. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1-8.
26. Ulf Teleman. 1974. Manual för grammatisk beskrivning av talad och skriven svenska. Studentlitteratur.
27. Vladimir Vapnik. 1995. The Nature of Statistical Learning Theory. Springer.
28. Vladimir Vapnik. 1998. Statistical Learning Theory. John Wiley and Sons, New York.
29. Volkan Vural and Jennifer G. Dy. 2004. A hierarchical method for multi-class support vector machines. ACM International Conference Proceeding Series, 69:105-113.
30. Ting-Fan Wu, Chih-Jen Lin, and Ruby C. Weng. 2004. Probability estimates for multi-class classification by pairwise coupling. Journal of Machine Learning Research, 5:975-1005.
31. Nianwen Xue, Fei Xia, Fu-Dong Chiou, and Martha Palmer. 2005. The Penn Chinese Treebank: Phrase structure annotation of a large corpus. Natural Language Engineering, 11(2):207-238.
32. Hiroyasu Yamada and Yuji Matsumoto. 2003. Statistical dependency analysis with support vector machines. In Proceedings of the 8th International Workshop on Parsing Technologies (IWPT), pages 195-206.