Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 890901, 14 pages
http://dx.doi.org/10.1155/2011/890901
Research Article

Structure Identification-Based Clustering According to Density Consistency

Chunzhong Li1,2 and Zongben Xu1,2

1Institute for Information and System Science, Xi'an Jiaotong University, Xi'an 710049, China
2Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an 710049, China

Received 22 March 2011; Revised 31 July 2011; Accepted 31 July 2011

Academic Editor: Wei-Chiang Hong

Copyright © 2011 Chunzhong Li and Zongben Xu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Structure of data set is of critical importance in identifying clusters, especially the density difference feature. In this paper, we present a clustering algorithm based on density consistency, which is a filtering process to identify same structure feature and classify them into same cluster. This method is not restricted by the shapes and high dimension data set, and meanwhile it is robust to noises and outliers. Extensive experiments on synthetic and real world data sets validate the proposed the new clustering algorithm.