• DocumentCode
    1528411
  • Title

    Visualizing text data sets

  • Author

    Booker, Andrew ; Condliff, Michelle ; Greaves, Mark ; Holt, Fred B. ; Kao, Anne ; Pierce, Daniel J. ; Poteet, Stephen ; Wu, Y.-J.J.

  • Author_Institution
    The Boeing Co., Seattle, WA, USA
  • Volume
    1
  • Issue
    4
  • fYear
    1999
  • Firstpage
    26
  • Lastpage
    35
  • Abstract
    The authors present a visualization methodology which provides users with a way to alter perspectives and interpret visualization so that they can quickly identify trends, outliers, and possible clusters while tuning for a particular context. The technology developed for text mining is called Trust, or Text Representation Using Subspace Transformation. Trust provides an analysis environment that can supply meaningful representations of text documents; it also supports the functional ability to visually present a collection of documents in a meaningful context that allows for user insight and textual content. Contrary to other similar technologies, Trust applies a novel analysis ability that allows different subspaces to generate views, providing content information for the basis of the visualization and allowing an analyst to specify subspaces for it based on content
  • Keywords
    data mining; data visualisation; text analysis; Text Representation Using Subspace Transformation; Trust; analysis ability; analysis environment; content information; outliers; subspaces; text data set visualization; text documents; text mining; textual content; user insight; visualization methodology; Consumer electronics; Data analysis; Data engineering; Data mining; Data visualization; Engines; Histograms; Information analysis; Scattering; Text mining;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/5992.774838
  • Filename
    774838