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