Fuzzy Clustering for Cooccurrence Matrix Using Possibilistic Constraint

Abstract

In this paper, we propose a new fuzzy clustering algorithm for cooccurrence matrix. In our proposal, the graded possibilistic approach is applied to estimation of memberships of items for deriving the absolute responsibilities of them. The memberships can be regarded as the probability that an experimental outcome coincides with one of mutually independent events. Then, soft transition of memberships from probabilistic to possibilistic constraint is performed by using the graded possibilistic constraint in the approach.