Presentation 2010-10-23
Extraction of Verb Synonyms Using Graph-Based Clustering
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This manuscript describes evaluation results of Kernel K-means clustering approach comparing with modified Aizawa's co-clustering approach for verb synonym extraction task. Kernel K-means approach is one of the state-of-the-art vector-based clustering method which can divide vector-spaces with non-linear boundary by incorporating Kernel method. Besides the mathematical framework of Kernel K-means can cover Spectral Graph Clustering. In this manuscript, however, we reveal Aizawa's co-clustering approach overcomes Kernel K-means on the verb synonym extraction task (bi-graph clustering) in Japanese. From this results we discuss that the equivalence between graph-vector space in Kernel K-means approach can be limited, and then Kernel K-means decease their accuracy in our verb synonym extraction.
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Keyword(in English) Verb synonyms / Co-clustering / Kernel K-means Clustering
Paper # TL2010-32,NLC2010-11
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Committee TL
Conference Date 2010/10/16(1days)
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Paper Information
Registration To Thought and Language (TL)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Extraction of Verb Synonyms Using Graph-Based Clustering
Sub Title (in English)
Keyword(1) Verb synonyms
Keyword(2) Co-clustering
Keyword(3) Kernel K-means Clustering
1st Author's Name Koichi TAKEUCHI
1st Author's Affiliation Graduate School of Natural Science, Okayama University()
2nd Author's Name Hideyuki TAKAHASHI
2nd Author's Affiliation Graduate School of Natural Science, Okayama University
3rd Author's Name Daisuke KOBAYASHI
3rd Author's Affiliation Department of Information Technology, Faculty of Engineering, Okayama University
Date 2010-10-23
Paper # TL2010-32,NLC2010-11
Volume (vol) vol.110
Number (no) 244
Page pp.pp.-
#Pages 6
Date of Issue