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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 589386, 6 pages
http://dx.doi.org/10.1155/2013/589386
Research Article

An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy

1School of Psychology, Liaoning Normal University, Dalian 116029, China
2School of Computer Science and Engineering, Aizu University, Aizuwakamatsu 965-8580, Japan

Received 26 February 2013; Accepted 23 April 2013

Academic Editor: Fuding Xie

Copyright © 2013 Yan Sun and Shuxue Ding. 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

The Wu-Huberman clustering is a typical linear algorithm among many clustering algorithms, which illustrates data points relationship as an artificial “circuit” and then applies the Kirchhoff equations to get the voltage value on the complex circuit. However, the performance of the algorithm is crucially dependent on the selection of pole points. In this paper, we present a novel pole point selection strategy for the Wu-Huberman algorithm (named as PSWH algorithm), which aims at preserving the merit and increasing the robustness of the algorithm. The pole point selection strategy is proposed to filter the pole point by introducing sparse rate. Experiments results demonstrate that the PSWH algorithm is significantly improved in clustering accuracy and efficiency compared with the original Wu-Huberman algorithm.