• DocumentCode
    2397666
  • Title

    On the enhanced multi-membership clustering Quasi-Clique Merger algorithm

  • Author

    Fuller, Edgar ; Tang, Wenliang ; Wu, Yezhou ; Zhang, Cun-Quan

  • Author_Institution
    Dept. of Math., West Virginia Univ., Morgantown, WV, USA
  • fYear
    2012
  • fDate
    19-20 May 2012
  • Firstpage
    244
  • Lastpage
    248
  • Abstract
    In this paper, we survey three enhanced versions of the Quasi-Clique Merger (QCM) algorithm for clustering data sets. By assigning a graphical structure to a data set, we cluster the underlying data by analyzing the graph and identifying dense subgraphs. In the current work we outline three variations of the QCM algorithm and illustrate their effectiveness on example data sets.
  • Keywords
    computer graphics; graph theory; pattern clustering; data sets clustering; dense subgraphs; enhanced multimembership clustering quasi-clique merger algorithm; graphical structure; Algorithm design and analysis; Bioinformatics; Cancer; Clustering algorithms; Educational institutions; Joining processes; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2012 International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4673-0198-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2012.6223558
  • Filename
    6223558