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