Applying rough set theory to information retrieval

Rough set theory is a useful mathematical tool that deals with vagueness and uncertainty in data. It has been applied to many computer scientific fields, such as data mining, machine learning, pattern recognition, and expert systems. The main objective of this paper is to investigate the applications of rough set theory in the field of information retrieval. By classifying and analyzing the existing approaches with regard to this topic, the advantages of using rough set theory become clear. Using rough set approach enables us to improve the information retrieval system performances in terms of document ranking, recall level and may provide more user oriented search strategies. Possible improvements are suggested as potential research directions.