• 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