• DocumentCode
    3134635
  • Title

    Homology graph mining for social network analysis

  • Author

    Gaol, Ford Lumban

  • Author_Institution
    Dept. of Grad. Program in Comput. Sci., Bina Nusantara Univ., Jakarta, Indonesia
  • fYear
    2011
  • fDate
    27-29 Dec. 2011
  • Firstpage
    269
  • Lastpage
    272
  • Abstract
    In this paper, we present a methodology, called Homology Graph Mining, for computer-aided extraction of Social Network rules from consolidated homology graphs of statements. First, we will generate homology sources of a set of heterogeneous social networks resources in terms of relevant pathway. Second, combine a homology graph by means of homology integration of the social network resources. Third, Search and Analyze patterns from the graph. Fourth, generate and evaluate a set of candidate social network rules, which are maintained and indexed for interactive discovery of actionable rules. As part of implementation efforts of the methodology, framework architecture of specialized interrelated knowledge discovery services is proposed, and an application in biomedicine is initiated.
  • Keywords
    data mining; graph theory; medical computing; social networking (online); biomedicine; computer aided social network rules extraction; homology graph mining; interactive actionable rules discovery; social network analysis; Grammar; Navigation; OWL; Ontologies; World Wide Web; Graph Mining; Homology; Social Networks; interrelated knowledge discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Education, Entertainment and e-Management (ICEEE), 2011 International Conference on
  • Conference_Location
    Bali
  • Print_ISBN
    978-1-4577-1381-1
  • Type

    conf

  • DOI
    10.1109/ICeEEM.2011.6137803
  • Filename
    6137803