A self-organized network for data clustering

Authors:
Liang Zhao;Antonio P. G. Damiance;Andre C. P. L. F. Carvalho
Affiliations:
Institute of Mathematics and Computer Science, University of São Paulo, Brazil;Institute of Mathematics and Computer Science, University of São Paulo, Brazil;Institute of Mathematics and Computer Science, University of São Paulo, Brazil
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

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Abstract

In this paper, a dynamical model for data clustering is proposed. This approach employs a network consisting of interacting elements with each representing an attribute vector of input data and receiving attractions from other elements within a certain region. Those attractions, determined by a predefined similarity measure, drive the elements to converge to their corresponding cluster center. With this model, neither the number of data clusters nor the initial guessing of cluster centers is required. Computer simulations for clustering of real images and Iris data set are performed. The results obtained so far are very promising.