• DocumentCode
    303197
  • Title

    Exploration of full-text databases with self-organizing maps

  • Author

    Honkela, Timo ; Kaski, Samuel ; Lagus, Krista ; Kohonen, Teuvo

  • Author_Institution
    Neural Networks Res. Centre, Helsinki Univ. of Technol., Espoo, Finland
  • Volume
    1
  • fYear
    1996
  • fDate
    3-6 Jun 1996
  • Firstpage
    56
  • Abstract
    Availability of large full-text document collections in electronic form has created a need for intelligent information retrieval techniques, especially the expanding World Wide Web which presupposes methods for systematic exploration of miscellaneous document collections. In this paper we introduce a new method, the WEBSOM, for this task. Self-organizing maps (SOMs) are used to represent documents on a map that provides an insightful view of the text collection. This view visualizes similarity relations between the documents, and the display can be utilized for orderly exploration of the material rather than having to rely on traditional search expressions. The complete WEBSOM method involves a two-level SOM architecture comprising of a word category map and a document map, and means for interactive exploration of the database
  • Keywords
    Internet; database theory; document handling; entropy; query processing; self-organising feature maps; unsupervised learning; WEBSOM; World Wide Web; document collections; document map; full-text databases; intelligent information retrieval; self-organizing maps; word category map; Databases; Displays; Encoding; Histograms; Information retrieval; Internet; Neural networks; Self organizing feature maps; Visualization; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1996., IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-3210-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1996.548866
  • Filename
    548866