ABSTRACT
In such cases, the computation of distance or similarity measures becomes essential to distinguish the similarity between two sets. These measures are very common in many applications that deal with matching-related problems. Suppose {a1 ,a2, a3, … , an) and {b1, b2, b3, … , bn) are two sets containing n elements. To fi nd the similarity between the two sets and hence the match value, fuzzy similarity, distance measure, measures of fuzziness, and entropy are calculated between fuzzy sets and fuzzy elements. These fuzzy measures are useful when we deal with fuzzy data. In fuzzy database and information retrieval, a query data is allowed to match with the data in the database and if the matching degree, that is, the similarity measure value, exceeds a prespecifi ed threshold, then the data is retrieved.
