Improving query expansion with stemming terms:: A new genetic algorithm approach

Nowadays, searching information in the wet) or in any kind of document collection has become one of the most frequent activities. However, user queries can be formulated in a way that hinder the recovery of the requested information. The objective of automatic query transformation is to improve the quality of the recovered information. This paper describes a new genetic algorithm used to change the set of terms that compose a user query without user supervision, by complementing an expansion process based on the use of a morphological thesaurus. We apply a stemming process to obtain the stem of a word, for which the thesaurus provides its different forms. The set of candidate query terms is constructed by expanding each term in the original query with the terms morphologically related. The genetic algorithm is in charge of selecting the terms of the final query from the candidate term set. The selection process is based on the retrieval results obtained when searching with different combination of candidate terms. We have obtained encouraging results, improving the performance of a standard set of tests.