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Query optimisation using an improved genetic algorithm
Author(s) -
Lynda Tamine,
Mohand Boughanem
Publication year - 2000
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-58113-320-0
DOI - 10.1145/354756.354842
Subject(s) - computer science , genetic algorithm , algorithm , machine learning
This paper presents an approach to intelligent information retrieval based on genetic heuristics. Recent search has shown that applying genetic models for query optimisation improve the retrieval effectiveness. We investigate ways to improve this process by combining genetic heuristics and information retrieval techniques. More precisely, we propose to integrate relevance feedback techniques to perform the genetic operators and the speciation heuristic to solve the relevance multimodality problem. Experiments, with AP documents and queries issued from TREC, showed the effectiveness of our approach. Keywords: Information

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