• DocumentCode
    1155409
  • Title

    Using projections to visually cluster high-dimensional data

  • Author

    Hinneburg, Alexander ; Keim, Daniel ; Wawryniuk, Markus

  • Author_Institution
    Halle-Wittenberg Univ., Germany
  • Volume
    5
  • Issue
    2
  • fYear
    2003
  • Firstpage
    14
  • Lastpage
    25
  • Abstract
    The High-Dimensional Eye system proves that a tight integration of advanced clustering algorithms and state-of-the-art visualization techniques can help us better understand and effectively guide the clustering process, and thus significantly improve the clustering results.
  • Keywords
    data mining; data visualisation; data warehouses; pattern clustering; High-Dimensional Eye system; clustering algorithms; projections; visual high dimensional data clustering; visualization techniques; Application software; Clustering algorithms; Data mining; Data visualization; Machine learning; Multidimensional systems; Particle separators; Partitioning algorithms; Statistics; Visual databases;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCISE.2003.1182958
  • Filename
    1182958
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1155409