Revue de l'Information Scientifique et Technique
Volume 27, Numéro 1, Pages 16-24
2023-05-08

Using Genetic Algorithms To Improve Information Retrieval



Authors : Bessai-mechmache Fatma Zohra . Alimazighi Zaia . Hammouche Karima .

Abstract

Finding the valuable relevant informat ion cont inues to be the major challenges of Informat ion Ret rieval Systems owing to the explosive growth of online web informat ion. Among these challenges, we consider the XML Informat ion Ret rieval challenges as XML has become a de facto standard over the Web. In this paper, we tackle the issue of content -based XML informat ion ret rieval. We formulate the ret rieval issue as a combinatorial opt imizat ion problem in order to generate the best set of relevant XML elements for a given keywords query. In our proposal, we define a genet ic algorithm which maximizes similarity between a set of XML elements and the user query. The results based on the precision measure are very promising.

Keywords

Genetic Algorithm ; Result Merging ; Crossover Operator ; Mutation Operator ; Information Retrieval ; XML Information Retrieval

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