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A Community Extraction Method using Intersection Graph and Semantic Analysis in Complex Network
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- KURAMOCHI Toshiya
- Graduate School of Engineering Science, Osaka University
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- OKADA Naoki
- Graduate School of Engineering Science, Osaka University
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- TANIKAWA Kyohei
- Graduate School of Engineering Science, Osaka University
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- HIJIKATA Yoshinori
- Graduate School of Engineering Science, Osaka University
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- NISHIDA Shogo
- Graduate School of Engineering Science, Osaka University
Bibliographic Information
- Other Title
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- 複雑ネットワークにおける交グラフと意味的解析を用いたコミュニティ発見手法
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Description
There is an increasing number of researches of complex networks such as World Wide Web, social networks and biological networks. They have found the property of a scale free, a small world, a large clustering coefficient, and so on. One of the hot topics in this area is community detection. Nodes belonging to a community are likely to have common properties. For instance, in the World Wide Web, a community may be a set of pages which belong to a same topic. Community structure is undoubtedly a key characteristic of complex networks. In this paper, we present a new framework for finding communities in complex networks and evaluate detecting the community. This framework uses the idea of intersection graph and uses semantic information such as text and attributes which appear in networks.
Journal
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- Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
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Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 25 (1), 540-555, 2013
Japan Society for Fuzzy Theory and Intelligent Informatics
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Details 詳細情報について
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- CRID
- 1390001205187487104
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- NII Article ID
- 130003368207
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- ISSN
- 18817203
- 13477986
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed