C4.5: programs for machine learning
C4.5: programs for machine learning
Using decision trees to construct a practical parser
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
A new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Three new probabilistic models for dependency parsing: an exploration
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Dependency parsing of Japanese spoken monologue based on clause boundaries
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Determining the Dependency Among Clauses Based on Machine Learning Techniques
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
SVM-based clause-dependency determination in syntactic analysis
ACS'06 Proceedings of the 6th WSEAS international conference on Applied computer science
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This paper proposes a statistical method for learning dependency preference of Japanese subordinate clauses, in which scope embedding preference of subordinate clauses is exploited as a useful information source for disambiguating dependencies between subordinate clauses. Estimated dependencies of subordinate clauses successfully increase the precision of an existing statistical dependency analyzer.