Presentation 2005-05-18
Fuzzy Clustering using Learned Type Multi-agent Model
Kenji SHIMIZU, Atsushi TSUYA, Atsushi TANAKA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In recent years, a lot in the individual in factors of the capacity improvement of the record media eq.Hard Disk and the spread of the Internet. The digital data which treats individually has increased. Therefore, the trouble such as not obtaining information for which information is a lot and is necessary even if it is done that necessary information is obtained can be found. It proposes the technique for the use of the Multi-agent Model and arranging it efficiently by various information. A peculiar user profile to the user is made, and it optimizes it to the user by the studied thing. It is thought that it is possible to use by this thing as assistance of information retrieval from various documents, and the problem in the clustering evaluation can be evaded.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Information Retrieval / Cluster Analysis / Multi-Agent
Paper # NLP2005-11
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Conference Information
Committee NLP
Conference Date 2005/5/11(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Fuzzy Clustering using Learned Type Multi-agent Model
Sub Title (in English)
Keyword(1) Information Retrieval
Keyword(2) Cluster Analysis
Keyword(3) Multi-Agent
1st Author's Name Kenji SHIMIZU
1st Author's Affiliation Science-and-engineering graduate course, Yamagata University()
2nd Author's Name Atsushi TSUYA
2nd Author's Affiliation Science-and-engineering graduate course, Yamagata University
3rd Author's Name Atsushi TANAKA
3rd Author's Affiliation Department of Information, Yamagata University
Date 2005-05-18
Paper # NLP2005-11
Volume (vol) vol.105
Number (no) 50
Page pp.pp.-
#Pages 4
Date of Issue