Title :
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
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;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900302
