ID | 19679 |
Eprint ID | 19679
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FullText URL | |
Author |
Yamaguchi Takehiro
Niimi Ayahiko
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Abstract | 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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Published Date | 2009-11-10
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Publication Title |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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Volume | volume2009
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Issue | issue1
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Publisher | IEEE SMC Hiroshima Chapter
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Start Page | 196
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End Page | 201
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ISSN | 1883-3977
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NCID | BB00577064
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Content Type |
Conference Paper
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language |
English
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Copyright Holders | IEEE SMC Hiroshima Chapter
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Event Title | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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Event Location | 東広島市
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Event Location Alternative | Higashi-Hiroshima City
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File Version | publisher
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Refereed |
True
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Eprints Journal Name | IWCIA
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