A document clustering algorithm for discovering and describing topics
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Altres documents de l'autoria: Anaya Sánchez, Henry; Pons Porrata, Aurora; Berlanga Llavori, Rafael
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http://dx.doi.org/10.1016/j.patrec.2009.11.013 |
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Títol
A document clustering algorithm for discovering and describing topicsData de publicació
2010Editor
ElsevierISSN
1678655Cita bibliogràfica
Pattern Recognition Letters, 31, 6, p. 502-510Tipus de document
info:eu-repo/semantics/articleParaules clau / Matèries
Resum
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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