Presentation 2001/5/4
Experiments on word sense disambiguation using several machine-learning methods
Masaki Murata, Masao Utiyama, Kiyotaka Uchimoto, Qing Ma, Hitoshi Isahara,
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Abstract(in English) In this research, we carried out experiments on Japanese word sense disambiguation in the RWC corpus by using the four machine-learning methods: the support-vector machine method, the maximum-entropy model method, the decision-list method, the simple Bayes method. The result was that the support-vector machine method produced the best precisions among them.
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Keyword(in English) Word Sense Disambiguation / Support Vector Machine / Japanese Language
Paper # NLC2001-2
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Conference Information
Committee NLC
Conference Date 2001/5/4(1days)
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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) Experiments on word sense disambiguation using several machine-learning methods
Sub Title (in English)
Keyword(1) Word Sense Disambiguation
Keyword(2) Support Vector Machine
Keyword(3) Japanese Language
1st Author's Name Masaki Murata
1st Author's Affiliation Keihanna Human Info-communication Research Center, Communications Ressearch Laboratory()
2nd Author's Name Masao Utiyama
2nd Author's Affiliation Keihanna Human Info-communication Research Center, Communications Ressearch Laboratory
3rd Author's Name Kiyotaka Uchimoto
3rd Author's Affiliation Keihanna Human Info-communication Research Center, Communications Ressearch Laboratory
4th Author's Name Qing Ma
4th Author's Affiliation Keihanna Human Info-communication Research Center, Communications Ressearch Laboratory
5th Author's Name Hitoshi Isahara
5th Author's Affiliation Keihanna Human Info-communication Research Center, Communications Ressearch Laboratory
Date 2001/5/4
Paper # NLC2001-2
Volume (vol) vol.101
Number (no) 40
Page pp.pp.-
#Pages 8
Date of Issue