A document clustering algorithm for discovering and describing topics
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Scholar |
Otros documentos de la autoría: Anaya Sánchez, Henry; Pons Porrata, Aurora; Berlanga Llavori, Rafael
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Mostrar el registro completo del ítemcomunitat-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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Título
A document clustering algorithm for discovering and describing topicsFecha de publicación
2010Editor
ElsevierISSN
1678655Cita bibliográfica
Pattern Recognition Letters, 31, 6, p. 502-510Tipo de documento
info:eu-repo/semantics/articlePalabras clave / Materias
Resumen
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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