Avoiding Premature Convergence of Genetic Algorithm in Informational Retrieval Systems

Abstract

Genetic algorithm is been adopted to implement information retrieval systems by many researchers to retrieve optimal document set based on user query. However, GA is been critiqued by premature convergence due to falling into local optimal solution. This paper proposes a new hybrid crossover technique that speeds up the convergence while preserving high quality of the retrieved documents. The proposed technique is applied to HTML documents and evaluated using precision measure. The results show that this technique is efficient in balancing between fast convergence and high quality outcome.

Authors and Affiliations

Ammar Sami Aldallal*| Ahlia University – Bahrain

Keywords

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  • EP ID EP759
  • DOI -
  • Views 489
  • Downloads 23

How To Cite

Ammar Sami Aldallal* (2014). Avoiding Premature Convergence of Genetic Algorithm in Informational Retrieval Systems. International Journal of Intelligent Systems and Applications in Engineering, 2(4), 80-85. https://europub.co.uk./articles/-A-759