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
Link To Document