Ultraconservative online algorithms for multiclass problems
The Journal of Machine Learning Research
Three new probabilistic models for dependency parsing: an exploration
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Online large-margin training of dependency parsers
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Pseudo-projective dependency parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Japanese dependency parsing using co-occurrence information and a combination of case elements
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Linear-time dependency analysis for Japanese
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Deterministic dependency parsing of English text
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
A pipeline approach for syntactic and semantic dependency parsing
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
A pipeline approach for syntactic and semantic dependency parsing
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Polynomial to linear: efficient classification with conjunctive features
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Using smaller constituents rather than sentences in active learning for Japanese dependency parsing
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Tree-based deterministic dependency parsing: an application to Nivre's method
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Mining rules for rewriting states in a transition-based dependency parser
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
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In Japanese dependency parsing, Kudo's relative preference-based method (Kudo and Matsumoto, 2005) outperforms both deterministic and probabilistic CKY-based parsing methods. In Kudo's method, for each dependent word (or chunk) a log-linear model estimates relative preference of all other candidate words (or chunks) for being as its head. This cannot be considered in the deterministic parsing methods. We propose an algorithm based on a tournament model, in which the relative preferences are directly modeled by one-on-one games in a step-ladder tournament. In an evaluation experiment with Kyoto Text Corpus Version 4.0, the proposed method outperforms previous approaches, including the relative preference-based method.