Community Detection Based on Surrogate Network

Lyu，Chao1,2; Shi，Yuhui2; Sun，Lijun2,3

10.1007/978-981-19-1253-5_4

2022

1865-0929

1865-0937

Communications in Computer and Information Science

1566 CCIS

45-53

This paper presents a novel methodology to detect communities in complex networks based on evolutionary computation. In the proposed method, a surrogate network with a more detectable community structure than the original network is firstly constructed based on the eigenmatrix of the adjacent matrix. Then the community partition can be found by successively optimizing the modularity of the surrogate network and the original network with an evolutionary algorithm. The proposed method is tested on both synthetic and real-world networks and compared with some existing algorithms. Experimental results show that employing the constructed surrogate networks can effectively improve the community detection efficiency.

Community detection Complex network Evolutionary computation

通讯

英语

EI

20221511956118

Evolutionary algorithms ; Matrix algebra ; Population dynamics

Computer Systems and Equipment:722 ; Algebra:921.1 ; Social Sciences:971

2-s2.0-85127884235

Scopus

1.Harbin Institute of Technology,Harbin,150001,China
2.Southern University of Science and Technology,Shenzhen,518055,China
3.University of Technology Sydney,Sydney,Australia

Lyu，Chao,Shi，Yuhui,Sun，Lijun. Community Detection Based on Surrogate Network[C],2022:45-53.