DocumentCode :
351017
Title :
Keyword selection method for characterizing text document maps
Author :
Lagus, Krista ; Kaski, Samuel
Author_Institution :
Neural Networks Res. Centre, Helsinki Univ. of Technol., Finland
Volume :
1
fYear :
1999
fDate :
1999
Firstpage :
371
Abstract :
Characterization of subsets of data is a recurring problem in data mining. We propose a keyword selection method that can be used for obtaining characterizations of clusters of data whenever textual descriptions can be associated with the data. Several methods that cluster data sets or form projections of data provide an order or distance measure of the clusters. If such an ordering of the clusters exists or can be deduced, the method utilizes the order to improve the characterizations. The proposed method may be applied, for example, to characterizing graphical displays of collections of data ordered (e.g. with SOM algorithm). The method is validated using a collection of 10000 scientific abstracts from the INSPEC database organized on a WEBSOM document map
Keywords :
information retrieval; INSPEC database; SOM algorithm; WEBSOM; data clusters; data mining; information retrieval; keyword selection; self organising map; text document maps;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)
Conference_Location :
Edinburgh
ISSN :
0537-9989
Print_ISBN :
0-85296-721-7
Type :
conf
DOI :
10.1049/cp:19991137
Filename :
819749
Link To Document :
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