Main Article Content
Abstract
This paper proposes a method to improve the performance of information retrieval
systems by expanding queries using genetic algorithm. The expansion terms are taken using
relevance feedback from user judgment process in response of document retrieved.
Experiment using international standard text collections (CISI, CACM and INSPEC
collection) which consist more than one thousand document each collection proved that this
method could improve the information retrieval. This method has been developed and tested
using Non Interpolated Average Precision (NAP) as an evaluation formula. The results of the
test are discussed, and some directions for further works are pointed out.
Keywords: Query expansion, information retrieval, term weighting, genetic algorithm,
document retrieval
systems by expanding queries using genetic algorithm. The expansion terms are taken using
relevance feedback from user judgment process in response of document retrieved.
Experiment using international standard text collections (CISI, CACM and INSPEC
collection) which consist more than one thousand document each collection proved that this
method could improve the information retrieval. This method has been developed and tested
using Non Interpolated Average Precision (NAP) as an evaluation formula. The results of the
test are discussed, and some directions for further works are pointed out.
Keywords: Query expansion, information retrieval, term weighting, genetic algorithm,
document retrieval