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Mathematical Problems in Engineering
Volume 2016, Article ID 3790590, 15 pages
http://dx.doi.org/10.1155/2016/3790590
Research Article

A Neighborhood-Impact Based Community Detection Algorithm via Discrete PSO

Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi’an 710038, China

Received 30 August 2015; Revised 6 December 2015; Accepted 31 December 2015

Academic Editor: Daniel Aloise

Copyright © 2016 Dongqing Zhou and Xing Wang. 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 paper addresses particle swarm optimization (PSO) into community detection problem, and an algorithm based on new label strategy is proposed. In contrast with other label propagation strategies, the main contribution of this paper is to design the definition of the impact of node and take it into use. Special initialization and update approaches based on it are designed in order to make full use of it. Experiments on synthetic and real-life networks show the effectiveness of proposed strategy. Furthermore, this strategy is extended to signed networks, and the corresponding objective function which is called modularity density is modified to be used in signed networks. Experiments on real-life networks also demonstrate that it is an efficacious way to solve community detection problem.