The possibilistic C-means algorithm (PCM) was proposed to address the drawbacks associated with the constrained memberships used in algorithms such as the fuzzy C-Means.Expand

We present a new clustering algorithm called Competitive Agglomeration (CA), which minimizes the objective function that incorporates the advantages of both hierarchical and partitional clustering and produces a sequence of partitions with a decreasing number of clusters.Expand

This paper addresses three major issues associated with conventional partitional clustering, namely, sensitivity to initialization, difficulty in determining the number of clusters, and sensitivity to noise and outliers.Expand

We provide a general overview of several methods for generating membership functions for fuzzy pattern recognition applications, and discuss the suitability and applicability of these membership function generation techniques to particular situations.Expand

The fuzzy c spherical shells clustering algorithm is specially designed to search for clusters that can be described by circular arcs or hyperspheres.Expand

We propose a new hierarchical monothetic clustering algorithm to build a topic hierarchy for a collection of search results retrieved in response to a query.Expand