Presentation 1998/7/23
Comparison of several statistical parsing methods for Japanese bunsetsu dependency
Terumasa EHARA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Several statistical methods for Japanese bunsetsu dependency analysis are compared. These methods are a) maximum entropy method, b) simplified maximum entropy method, c) decision tree method and d) WINNOW algorithm method. The base line method uses two features: 1)distance between dependant and head, 2)type of head. The bunsetsu dependency accuracy for these methods are a) 89.0% b) 88.3% c) 86.5% and) 85.9% compared with the base line accuracy 86.2%. These result is obtained by open test for the GA-case-bunsetsu (subject phrase) dependency in TV news articles.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Japanese bunsetsu dependency analysis / statistical method / maximum entropy / decision tree / WINNOW algorithm
Paper # NLC98-10
Date of Issue

Conference Information
Committee NLC
Conference Date 1998/7/23(1days)
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Place (in English)
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Topics (in English)
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Paper Information
Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Comparison of several statistical parsing methods for Japanese bunsetsu dependency
Sub Title (in English)
Keyword(1) Japanese bunsetsu dependency analysis
Keyword(2) statistical method
Keyword(3) maximum entropy
Keyword(4) decision tree
Keyword(5) WINNOW algorithm
1st Author's Name Terumasa EHARA
1st Author's Affiliation NHK Science and Technical Research Laboratories()
Date 1998/7/23
Paper # NLC98-10
Volume (vol) vol.98
Number (no) 209
Page pp.pp.-
#Pages 6
Date of Issue