Community detection based on modularity density and genetic algorithm

doi:10.1109/CASoN.2010.14

CORC > 兰州理工大学 > 兰州理工大学

	Community detection based on modularity density and genetic algorithm
	Liu, Jinxia 1,2; Zeng, Jianchao 2
	2010
关键词	Complex networks Population dynamics Structural optimization Community detection Community detection algorithms Community structures Community-based D values Extremal optimization Modularity densities
DOI	10.1109/CASoN.2010.14
页码	29-32
英文摘要	Detecting and characterizing the community structure of complex network and social network is fundamental problem. Many of the proposed algorithm for detecting community based on modularity Q which fail to identify modules smaller than a scale community. In this paper, authors propose a new community detection algorithm based on genetic algorithm and modularity density (D value). We test our method on classical social networks whose community structure is already known and the results can be much easier compared with the method. Experiments show the capability of the method to successfully detect the community structure. © 2010 IEEE.
会议录	Proceedings - International Conference on Computational Aspects of Social Networks, CASoN'10
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116805]
专题	兰州理工大学
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China; 2.Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan, China
推荐引用方式 GB/T 7714	Liu, Jinxia,Zeng, Jianchao. Community detection based on modularity density and genetic algorithm[C]. 见:.