A compression optimization algorithm for community detection

Author

Jianshe Wu ; Lin Yuan ; Qingliang Gong ; Wenping Ma ; Jingjing Ma ; Yangyang Li

Author_Institution

Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi´an, China

fYear

2014

fDate

6-11 July 2014

Firstpage

667

Lastpage

671

Abstract

Community detection is important in understanding the structures and functions of complex networks. Many algorithms have been proposed. The most popular algorithms detect the communities through optimizing a criterion function known as modularity, which suffer from the resolution limit problem. Some algorithms require the number of communities as a prior. In this paper, a non-modularity based compression optimization algorithm for community detection is proposed without any prior knowledge, which is efficient and is suitable for large scale networks.

Keywords

complex networks; large-scale systems; network theory (graphs); optimisation; community detection; complex networks; compression optimization algorithm; criterion function; large scale networks; modularity function; resolution limit problem; Algorithm design and analysis; Communities; Complex networks; Heuristic algorithms; Memetics; Optimization; Partitioning algorithms; community detection; complex networks; compression optimazation;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2014 IEEE Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4799-6626-4

Type

conf

DOI

10.1109/CEC.2014.6900302

Filename

6900302