C4.5: programs for machine learning
C4.5: programs for machine learning
Bagging and boosting a treebank parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Using decision trees to construct a practical parser
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Automatic corpus-based Thai word extraction with the c4.5 learning algorithm
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Chunking with support vector machines
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Japanese dependency structure analysis based on support vector machines
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Boosting trees for clause splitting
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Boosting for named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
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The detection of a gap in relative clauses is essential in syntactic and semantic analysis of natural language processing. This paper proposes automatic relative clause classification method based on various machine learning algorithms, and compare the classification performances of relative clauses. We use easily obtainable features that can be extracted from any language. We also analyze the contribution of each feature to the performance.