• DocumentCode
    2331991
  • Title

    The shape of Shakespeare: visualizing text using implicit surfaces

  • Author

    Rohrer, Randall M. ; Ebert, David S. ; Sibert, John L.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA
  • fYear
    1998
  • fDate
    19-20 Oct 1998
  • Firstpage
    121
  • Abstract
    Information visualization focuses on the use of visual means for exploring non-visual information. While free-form text is a rich, common source of information, visualization of text is a challenging problem since text is inherently non-spatial. The paper explores the use of implicit surface models for visualizing text. The authors describe several techniques for text visualization that aid in understanding document content and document relationships. A simple method is defined for mapping document content to shape. By comparing the shapes of multiple documents, global content similarities and differences may be noted. In addition, they describe a visual clustering method in which documents are arranged in 3D based upon similarity scoring. Documents deemed closely related blend together as a single connected shape. Hence, a document corpus becomes a collection of shapes that reflect inter-document relationships. These techniques provide methods to visualize individual documents as well as corpus meta-data. They then combine the two techniques to produce transparent clusters enclosing individual document shapes. This provides a way to visualize both local and global contextual information. Finally, they elaborate on several potential applications of these methods
  • Keywords
    data visualisation; text analysis; 3D arrangement; connected shape; corpus meta-data; document content; document content mapping; document corpus; document relationships; free-form text; global content differences; global content similarities; global contextual information; implicit surfaces; information visualization; inter-document relationships; local contextual information; nonvisual information; shape; similarity scoring; text visualization; transparent clusters; visual clustering method; Amorphous materials; Animation; Humans; Information analysis; Navigation; Neural networks; Scattering; Self organizing feature maps; Shape control; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Visualization, 1998. Proceedings. IEEE Symposium on
  • Conference_Location
    Research Triangle, CA
  • Print_ISBN
    0-8186-9093-3
  • Type

    conf

  • DOI
    10.1109/INFVIS.1998.729568
  • Filename
    729568