A novel clustering algorithm based upon a SOFM neural network family

Abstract

A novel clustering algorithm based upon a SOFM neural network family is proposed in this paper. The algorithm takes full advantage of the characteristics of SOFM Neural Network family and defines a novel similarity measure, topological similarity, which help the clustering algorithm to handle the clusters with arbitrary shapes and avoid suffering from the limitations of the conventional clustering algorithms. The paper suggests another novel thought to tackle the clustering problem. © Springer-Verlag Berlin Heidelberg 2005.