Fuzzy Logic Based Similarity Measure for Information Retrieval System Performance Improvement

The documents of any information retrieval system are ranked on the basis of similarity measure. Some similarity measures e. g. Cosine, Euclidean and Okapi etc. have been extensively used for retrieving relevant documents against the query. In present paper, a new fuzzy based similarity measure is proposed. Experiments have been performed on CACM data collection. The performance of proposed similarity measure is evaluated and compared with above mentioned similarity measures on the basis of Precision-Recall curves, average similarity value of documents for individual query and average number of retrieved relevant documents. The results show the marked improvement in performance of information retrieval system using proposed fuzzy logic based similarity as compare to other similarity measures.