Institute of Information Theories and Applications FOI ITHEA
This paper presents an adaptive method using genetic algorithm to modify user’s queries, based on
relevance judgments. This algorithm was adapted for the three well-known documents collections (CISI, NLP and
CACM). The method is shown to be applicable to large text collections, where more relevant documents are
presented to users in the genetic modification. The algorithm shows the effects of applying GA to improve the
effectiveness of queries in IR systems. Further studies are planned to adjust the system parameters to improve
its effectiveness. The goal is to retrieve most relevant documents with less number of non-relevant documents
with respect to user's query in information retrieval system using genetic algorithm.