Uncovering the fuzzy community structure accurately based on steepest descent projection

Author:

Fang Changjian1,Mu Dejun1,Deng Zhenghong1,Yan Jiaqi2

Affiliation:

1. School of Automation, Northwestern Polytechnical University, Shenzhen Research Institute, Xi’an, China

2. School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China

Abstract

Uncovering the community structure in complex network is a hot research point in recent years. How to identify the community structure accurately in complex network is still an open question under research. There are lots of methods based on topological information, which have some good performances at the expense of longer runtimes. In this paper, we propose a new fuzzy algorithm which follows the line of fuzzy c-means algorithm. A steepest descent framework with projection by optimizing the quality function is presented under the generalized framework. The results of experiments on both real-world networks and synthetic networks show that the proposed method achieves the highest efficiency and is easy for detecting fuzzy community structure in large-scale complex networks.

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

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