Group Method of Documentary Collections Using Genetic Algorithms

  • Authors:

  • José Luis Castillo S.;José R. Castillo;León González Sotos

  • Affiliations:

  • Department of Computer Science, University of Alcalá, Alcalá de Henares, Madrid, Spain 28871;Department of Computer Science, University of Alcalá, Alcalá de Henares, Madrid, Spain 28871;Department of Computer Science, University of Alcalá, Alcalá de Henares, Madrid, Spain 28871

  • Venue:
  • IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
  • Year:
  • 2009

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Abstract

We present a method of grouping documents with genetic algorithms, the groups are created from the tokens representing the document. The system select the tokens starting from the Goffman point, selecting an area of suitable transition making use for it of the Zipf law. The experiments are carried out with the collection Reuters 21578 and the genetic algorithm uses the new operators designed to find the affinity and similarity of the documents without having prior knowledge of other characteristics. The proposed method is an alternative to the methods of traditional clustering and the results show that genetic algorithm is robust, clustering the documents in the collection of documents efficiently.