• DocumentCode
    2754750
  • Title

    A Visual Approach for Spatio-Temporal Data Mining

  • Author

    Kechadi, M-Tahar ; Bertolotto, Michela

  • Author_Institution
    Sch. of Comput. Sci. & Informatics, Univ. Coll. Dublin
  • fYear
    2006
  • fDate
    16-18 Sept. 2006
  • Firstpage
    504
  • Lastpage
    509
  • Abstract
    In this paper, we propose a system for mining very large spatio-temporal datasets. The system comprises new techniques to efficiently support the data-mining process, address the spatial and temporal dimensions of the dataset, and visualize and interpret results. In particular, we have developed an advanced visualization tool for flexible and intuitive interaction with the dataset, including functionality for displaying association rules and variable distributions
  • Keywords
    data mining; data visualisation; visual databases; association rule; knowledge discovery; spatio-temporal data mining; visualization tool; Algorithm design and analysis; Computer science; Data analysis; Data mining; Data visualization; Educational institutions; Engines; Informatics; Pattern analysis; Shape control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Reuse and Integration, 2006 IEEE International Conference on
  • Conference_Location
    Waikoloa Village, HI
  • Print_ISBN
    0-7803-9788-6
  • Type

    conf

  • DOI
    10.1109/IRI.2006.252465
  • Filename
    4018542