A Local Dynamic Community Detection Algorithm Based on Node Contribution - Details

author：

Guo, K. (Guo, K..) ^[1] | He, L. (He, L..) ^[2] | Huang, J. (Huang, J..) ^[3] | Chen, Y. (Chen, Y..) ^[4] | Lin, B. (Lin, B..) ^[5]

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Scopus

Abstract：

The　existence　of　communities　in　various　complex　networks　is　ubiquitous　in　all　aspects　of　people’s　living.　Hence,　it　is　crucial　to　uncover　communities　accurately,　which　is　one　of　the　hottest　research　areas　in　the　field　of　network　analysis.　Particularly,　complex　networks　are　usually　in　continuous　change　so　that　it　is　more　realistic　to　uncover　dynamic　communities.　In　this　study,　an　algorithm　based　on　node　contribution　for　uncovering　dynamic　communities　is　proposed.　Firstly,　the　seed　nodes　are　selected　via　node　local　fitness　in　the　network,　thus　guaranteeing　that　the　selected　seeds　are　central　nodes　of　communities.　Secondly,　a　static　algorithm　is　used　to　obtain　communities　in　initial　snapshot　of　the　network.　Finally,　node　contribution　is　proposed　to　incrementally　uncover　communities　in　non-initial　snapshots　of　the　network.　The　experimental　results　reveal　that　our　method　outperforms　all　other　comparison　algorithms　in　both　artificial　and　real　datasets.　©　2019,　Springer　Nature　Singapore　Pte　Ltd.

Keyword：

Complex network; Dynamic community detection; Node contribution; Node local fitness

Community：

[ 1 ] [Guo, K.]College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou, 350116, China
[ 2 ] [Guo, K.]Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
[ 3 ] [Guo, K.]Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou, 350116, China
[ 4 ] [He, L.]College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou, 350116, China
[ 5 ] [He, L.]Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
[ 6 ] [He, L.]Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou, 350116, China
[ 7 ] [Huang, J.]Power Science and Technology Corporation State Grid Information and Telecommunication Group, Fuzhou, 351008, China
[ 8 ] [Chen, Y.]College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou, 350116, China
[ 9 ] [Chen, Y.]Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
[ 10 ] [Chen, Y.]Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou, 350116, China
[ 11 ] [Lin, B.]College of Physics and Energy, Fujian Provincial Key Laboratory of Quantum Manipulation and New Energy Materials, Fujian Normal University, Fuzhou, 350117, China

Reprint 's Address：

[Chen, Y.]College of Mathematics and Computer Sciences, Fuzhou UniversityChina

Email：

yzchen@fzu.edu.cn

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Source ：

Communications in Computer and Information Science

ISSN： 1865-0929

Year： 2019

Volume： 1042 CCIS

Page： 363-376

Language： English

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SCOPUS Cited Count： 3

ESI Highly Cited Papers on the List： 0 Unfold All

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Chinese Cited Count：

30 Days PV： 1

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