A local quantitative measure for community detection in networks. (4th June 2010)

• Record Type: Journal Article
• Authors: Yang, Shuzhong; Luo, Siwei
• Is Part Of: International journal of intelligent engineering informatics. Volume 1: Number 1 (2010)
• Page Start: 38
• Page End: 52
• Publication Date: 2010-06-04
• Subjects: community detection -- resolution limit -- normalised modularity density -- NMD -- modularity Q -- simulated annealing -- optimisation; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

Abstract

Recently, it has been proved that the resolution of methods based on optimising the modularity Q is limited. In order to improve this limit, a novel local quantitative measure called normalised modularity density NMD is proposed and optimised by simulated annealing technique. Both theoretical certifications on some schematic examples and numerical results on a suit of computer-generated and real-world networks show that optimising NMD can detect communities with different scales, especially small dense communities that optimising Q cannot detect, which provides meaningful evidence that optimising NMD can improve the resolution limit in optimising modularity Q.