ID | 19679 |
Eprint ID | 19679
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フルテキストURL | |
著者 |
Yamaguchi Takehiro
Future University-Hakodate
Niimi Ayahiko
Future University-Hakodate
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抄録 | Recently, there has been increasing interest in data analysis for network structured data. The network structured data is represented the relation between one data and other data by graph structure. There are many network structured data such as social networks, biological networks in the real world. In this study, we will analysis the network structured data that has dynamic relation and complex interact with each data. And, we will approach the problem that is to extract transition pattern from the history of temporal change in their network structured data. Especially, in this paper, we will apply community graph sequences to graph sequences of network structured data that has large-scale and complex changes, and propose the method of extracting transition pattern of network structured data. We used social bookmark data as the data streams of analysis object and verified that social bookmark data is the network structured data that has large-scale and complex change.
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発行日 | 2009-11-10
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出版物タイトル |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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巻 | 2009巻
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号 | 1号
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出版者 | IEEE SMC Hiroshima Chapter
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開始ページ | 196
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終了ページ | 201
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ISSN | 1883-3977
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NCID | BB00577064
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資料タイプ |
会議発表論文
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言語 |
英語
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著作権者 | IEEE SMC Hiroshima Chapter
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イベント | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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イベント地 | 東広島市
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イベント地の別言語 | Higashi-Hiroshima City
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論文のバージョン | publisher
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査読 |
有り
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Eprints Journal Name | IWCIA
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