• DocumentCode
    19245
  • Title

    Capturing Social Data Evolution Using Graph Clustering

  • Author

    Giatsoglou, Maria ; Vakali, Athena

  • Author_Institution
    Aristotle Univ., Thessaloniki, Greece
  • Volume
    17
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan.-Feb. 2013
  • Firstpage
    74
  • Lastpage
    79
  • Abstract
    The fast and unpredictable evolution of social data poses challenges for capturing user activities and complex associations. Evolving social graph clustering promises to uncover the dynamics of latent user and content patterns. This Web extra overviews evolving data clustering approaches.
  • Keywords
    data handling; graph theory; pattern clustering; social networking (online); capturing social data evolution; complex associations; data clustering; social graph clustering; Adaptation models; Clustering algorithms; Complexity theory; Data models; Internet; Web mining; clustering; data structures; database applications; database management; graphs and networks; information search and retrieval; mining methods and algorithms; pattern recognition;
  • fLanguage
    English
  • Journal_Title
    Internet Computing, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7801
  • Type

    jour

  • DOI
    10.1109/MIC.2012.141
  • Filename
    6415918