A document clustering algorithm for discovering and describing topics
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Other documents of the author: Anaya Sánchez, Henry; Pons Porrata, Aurora; Berlanga Llavori, Rafael
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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http://dx.doi.org/10.1016/j.patrec.2009.11.013 |
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Title
A document clustering algorithm for discovering and describing topicsDate
2010Publisher
ElsevierISSN
1678655Bibliographic citation
Pattern Recognition Letters, 31, 6, p. 502-510Type
info:eu-repo/semantics/articleSubject
Abstract
In this paper, we introduce a new clustering algorithm for discovering and describing the topics comprised in a text collection. Our proposal relies on both the most probable term pairs generated from the collection ... [+]
In this paper, we introduce a new clustering algorithm for discovering and describing the topics comprised in a text collection. Our proposal relies on both the most probable term pairs generated from the collection and the estimation of the topic homogeneity associated to these pairs. Topics and their descriptions are generated from those term pairs whose support sets are homogeneous enough for representing collection topics. Experimental results obtained over three benchmark text collections demonstrate the effectiveness and utility of this new approach. © 2009. [-]
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