Abstract: Information retrieval process is an inference for the real-world user communication, which is based on the concept of storing, representing and searching information. Moreover, it utilizes the repository in order to retrieve the stored information in an effective way. The processing of such system is not an easy task; also, its complexity depends on the quality of searched information. The information that would be retrieved depends on the query formed by the user. The fuzziness of human brain is extremely high as every person has different cognitive skills, opinions, thinking, perception, situation, intention, intuition and domain; these varied attributes results in a fuzzy query by the user for any information need, thus it can be said that different types of user have different query apprehension. In order to provide efficient and relevant results to the user according to the information need, the foremost requirement is to understand the users’ query. In this paper, hybrid of Vector Space Model with fuzzy logic inference has been implemented. The purpose of the system is mapping of the Vector Space Model with cognitive skills of the user using the fuzzy approach. The similarity between the documents has been computed using the fuzzy logic in order to evaluate the query results based on the graininess of the user.
