DocumentCode :
2732080
Title :
Discovering and Visualizing Network Communities
Author :
Murata, Tsuyoshi ; Takeichi, Koji
Author_Institution :
Tokyo Inst. of Technol., Tokyo
fYear :
2007
fDate :
5-12 Nov. 2007
Firstpage :
217
Lastpage :
220
Abstract :
There are several large-scale entities that are related with each other. Web hyperlink networks, social networks and metabolic networks are the examples of such networks. Discovering dense subnetworks (communities) from given networks is important for detecting macroscopic and microscopic structures. Although many discovery methods are proposed, qualitative and quantitative differences among them are not fully discussed. As the first step for interactive analysis of network structures, the authors are developing a system for discovering and visualizing network communities. The system has abilities for divisive and agglomerative discovery of communities from given networks based on modularity.
Keywords :
Internet; data mining; data visualisation; Web hyperlink networks; Web mining; metabolic networks; network community discovery; network community visualization; social networks; Biochemistry; Communities; Conferences; Data visualization; Intelligent agent; Intelligent networks; Large-scale systems; Microscopy; Social network services; Web mining; community discoveryvisualizationbetweennessmodularity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology Workshops, 2007 IEEE/WIC/ACM International Conferences on
Conference_Location :
Silicon Valley, CA
Print_ISBN :
0-7695-3028-1
Type :
conf
DOI :
10.1109/WI-IATW.2007.49
Filename :
4427575
Link To Document :
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