Summary: Efficient and effective text retrieval techniques are imperative in managing the increasing amount of textual information available in electronic form. Most existing text retrieval techniques rely on indexing keywords. Unfortunately, keywords or index terms alone cannot adequately capture the document contents, resulting in poor retrieval performance. One possible approach to solve this problem can be by using the vector space model, which models user request and database documents as vectors in the term space. The components of the vectors are determined by some existing popular term weighting schemes. A few new term weighting schemes are suggested which improves performance. The query document vector is then compared with the vectors of the documents in the database to determine which document aligns properly with the user request. The matching process is based on some similarity measure. This paper proposes a fuzzy similarity measure to retrieve the relevant documents from the database.