Presentation 2001/7/9
Word Sense Disambiguation based onFeature Space Restructuring
Hiroya Takamura, Hiroyasu Yamada, Taku Kudoh, Kaoru Yamamoto, Yuji Matsumoto,
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Abstract(in English) We propose a new method for Word Sense Disambiguation. In the proposed method, weighted majority voting method is applied for the several restructured feature space computed by Independent Component Analysis (ICA) or Principal Component Analysis (PCA). We also conducted some experiments with SENSEVAL data. This voting method is not specific to WSD and can be applied to various tasks.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) word sense / disambiguation / Indepedent Component Analysis / Support Vector Machines / unlabeled data / feature space
Paper # NLC2001-20
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Conference Information
Committee NLC
Conference Date 2001/7/9(1days)
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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) Word Sense Disambiguation based onFeature Space Restructuring
Sub Title (in English)
Keyword(1) word sense
Keyword(2) disambiguation
Keyword(3) Indepedent Component Analysis
Keyword(4) Support Vector Machines
Keyword(5) unlabeled data
Keyword(6) feature space
1st Author's Name Hiroya Takamura
1st Author's Affiliation Nara Institute of Science and Technology Graduate School of Information Science()
2nd Author's Name Hiroyasu Yamada
2nd Author's Affiliation Nara Institute of Science and Technology Graduate School of Information Science
3rd Author's Name Taku Kudoh
3rd Author's Affiliation Nara Institute of Science and Technology Graduate School of Information Science
4th Author's Name Kaoru Yamamoto
4th Author's Affiliation Nara Institute of Science and Technology Graduate School of Information Science
5th Author's Name Yuji Matsumoto
5th Author's Affiliation Nara Institute of Science and Technology Graduate School of Information Science
Date 2001/7/9
Paper # NLC2001-20
Volume (vol) vol.101
Number (no) 189
Page pp.pp.-
#Pages 8
Date of Issue