A New Document Clustering Algorithm for Topic Discovering and Labeling

  • Henry Anaya-Sánchez
  • Aurora Pons-Porrata
  • Rafael Berlanga-Llavori
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)

Abstract

In this paper, we introduce a new clustering algorithm for obtaining labeled document clusters that accurately identify the topics of a text collection. In order to determine the topics, our approach relies on both probable term pairs generated from the collection and the estimation of the topic homogeneity associated to term pair clusters. Experimental results obtained over two benchmark text collections demonstrate the utility of this new approach.

Keywords

document clustering topic discovery topic descriptions 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Henry Anaya-Sánchez
    • 1
  • Aurora Pons-Porrata
    • 1
  • Rafael Berlanga-Llavori
    • 2
  1. 1.Center for Pattern Recognition and Data MiningUniversidad de OrienteSantiago de CubaCuba
  2. 2.Department of Languages and Computer SystemsUniversitat Jaume ICastellóSpain

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