Document Clustering into an Unknown Number of Clusters Using a Genetic Algorithm

  • A. Casillas
  • M. T. González de Lena
  • R. Martínez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2807)

Abstract

We present a genetic algorithm that deals with document clustering. This algorithm calculates an approximation of the optimum k value, and solves the best grouping of the documents into these k clusters. We have evaluated this algorithm with sets of documents that are the output of a query in a search engine. The experiments show that, most of the times, our genetic algorithm obtains better values of the fitness function than the well known Calinski and Harabasz stopping rule, and takes less time.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • A. Casillas
    • 1
  • M. T. González de Lena
    • 2
  • R. Martínez
    • 2
  1. 1.Dpt. Electricidad y ElectrónicaUniversidad del País Vasco 
  2. 2.Dpt. Informática, Estadística y TelemáticaUniversidad Rey Juan Carlos 

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