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 :
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