• DocumentCode
    2370256
  • Title

    Icon-based visualization of large high-dimensional datasets

  • Author

    Chen, Ping ; Hu, Chenyi ; Ding, Wei ; Lynn, Heloise ; Simon, Yves

  • Author_Institution
    Dept. of Comput. & Math. Sci., Univ. of Houston, TX, USA
  • fYear
    2003
  • fDate
    19-22 Nov. 2003
  • Firstpage
    505
  • Lastpage
    508
  • Abstract
    High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional data. We divide dimensions of data into several groups. Then, we use one icon to represent each group, and associate visual properties of each icon with dimensions in each group. A high dimensional data record will be represented by multiple different types of icons located in the same position. Furthermore, we use summary icons to display local details of viewer´s interests and the whole data set at meantime. We show its effectiveness and efficiency through a case study on a real large data set.
  • Keywords
    data visualisation; graphical user interfaces; knowledge acquisition; rendering (computer graphics); very large databases; data analysts; high dimensional data record; high dimensional data visualization; icon visual properties; icon-based visualization; summary icons; Data analysis; Data mining; Data visualization; Displays; Histograms; Humans; Pattern recognition; Rendering (computer graphics); Scattering; Shape control;
  • 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.2003.1250963
  • Filename
    1250963