• DocumentCode
    1551740
  • Title

    Discovery visualization using fast clustering

  • Author

    Ribarsky, William ; Katz, Jochen ; Jiang, Frank ; Holland, Aubrey

  • Author_Institution
    Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    19
  • Issue
    5
  • fYear
    1999
  • Firstpage
    32
  • Lastpage
    39
  • Abstract
    To attack the problem of handling increasingly vast stores of information, we discuss a new approach to data exploration that requires the close coupling of man and machine. We call this approach discovery visualization to emphasize the importance of visual display and interaction. This approach aims to discover new relations, new features, and new knowledge. A key element in discovery visualization lies in heightening the machine´s awareness of users so they have, for example, focus-based manipulation, based on where and how closely they look at the displayed scene, in addition to direct manipulation. This process makes no sense unless the machine can respond immediately. Further, we promote the concept of continuous interaction with constant feedback between man and machine, and constant unfolding of the data. Finally, automated response must combine with user selection to achieve and sustain animated action, even in data sets of great or varying complexity
  • Keywords
    data mining; data visualisation; very large databases; automated response; continuous interaction; data exploration; data mining; data sets; direct manipulation; discovery visualization; fast clustering; focus-based manipulation; very large database; visual display; Animation; Clustering algorithms; Data visualization; Displays; Feature extraction; NP-complete problem; Neural networks; Shape; Silver; Simulated annealing;
  • fLanguage
    English
  • Journal_Title
    Computer Graphics and Applications, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1716
  • Type

    jour

  • DOI
    10.1109/38.788796
  • Filename
    788796