• DocumentCode
    2370518
  • Title

    PixelMaps: a new visual data mining approach for analyzing large spatial data sets

  • Author

    Keim, Daniel A. ; Panse, Christian ; Sips, Mike ; North, Stephen C.

  • Author_Institution
    Konstanz Univ., Germany
  • fYear
    2003
  • fDate
    19-22 Nov. 2003
  • Firstpage
    565
  • Lastpage
    568
  • Abstract
    PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kernel-density-based clustering with pixel-oriented displays to emphasize clusters while avoiding overlap in locally dense point sets on maps. Because a full evaluation of density functions is prohibitively expensive, we also propose an efficient approximation, Fast-PixelMap, based on a synthesis of the quadtree and gridfile data structures.
  • Keywords
    approximation theory; data mining; data visualisation; quadtrees; spatial data structures; visual databases; PixelMap algorithm; fast-PixelMap approximation; gridfile data structure; kernel-density-based clustering; pixel-oriented display; pixel-oriented visual data mining technique; quadtree synthesis; spatial data set analysis; visual data mining; Clustering algorithms; Computer displays; Credit cards; Data analysis; Data mining; Data structures; Data visualization; Density functional theory; Grid computing; Laboratories;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
  • Print_ISBN
    0-7695-1978-4
  • Type

    conf

  • DOI
    10.1109/ICDM.2003.1250978
  • Filename
    1250978