• DocumentCode
    2456101
  • Title

    Map-TreeMaps: A New Approach for Hierarchical and Topological Clustering

  • Author

    Azzag, Hanene ; Lebbah, Mustapha ; Arfaoui, Aymen

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Paris 13, Villetaneuse, France
  • fYear
    2010
  • fDate
    12-14 Dec. 2010
  • Firstpage
    873
  • Lastpage
    878
  • Abstract
    We present in this paper a new clustering method which provides self-organization of hierarchical clustering. This method represents large datasets on a forest of original trees which are projected on a simple 2D geometric relationship using tree map representation. The obtained partition is represented by a map of tree maps, which define a tree of data. In this paper, we provide the rules that build a tree of node/data by using distance between data in order to decide where connect nodes. Visual and empirical results based on both synthetic and real datasets from the UCI repository, are given and discussed.
  • Keywords
    data visualisation; geometry; pattern clustering; self-organising feature maps; 2D geometric relationship; hierarchical clustering; topological clustering; tree map representation; Clustering algorithms; Cost function; Data visualization; Indexes; Numerical models; Organizations; Visualization; Hierarchical clustering; Self-Organizing-Map; Treemaps; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-9211-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2010.136
  • Filename
    5708959