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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Committee | NLP |
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Conference Date | 2005/5/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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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 |
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