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An Estimation of Distribution Algorithms Applied to Sequence Pattern Mining

  • Paulo Igor A. Godinho
  • Aruanda S. Gonçalves Meiguins
  • Roberto C. Limão de Oliveira
  • Bianchi S. Meiguins
Conference paper
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Abstract

This paper presents a proposal of distribution’s estimated algorithm to the extraction of sequential patterns in a database which use a probabilistic model based on graphs which represent the relations among items that form a sequence. The model maps a probability among the items allowing them to adjust the model during the execution of the algorithm using the evolution process of EDA, optimizing the candidate’s generation of solution and extracting a group of sequential patterns optimized.

Keywords

Probabilistic Model Sequential Pattern Minimum Support Pattern Mining Frequent Sequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Paulo Igor A. Godinho
    • 1
  • Aruanda S. Gonçalves Meiguins
    • 1
    • 2
  • Roberto C. Limão de Oliveira
    • 1
  • Bianchi S. Meiguins
    • 1
  1. 1.Universidade Federal do Pará – UFPABelémBrazil
  2. 2.Centro Universitário do Pará – CESUPABelémBrazil

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