Evidential method to identify influential nodes in complex networks

doi:10.1109/JSEE.2015.00044

Journal of Systems Engineering and Electronics

• SOFTWARE ALGORITHM AND SIMULATION • Previous Articles Next Articles

Evidential method to identify influential nodes in complex networks

Hongming Mo^1,2, Cai Gao¹, and Yong Deng^1,3,4,*

1. School of Computer and Information Science, Southwest University, Chongqing 400715, China;
2. Department of the Tibetan Language, Sichuan University of Nationalities, Kangding 626001, China;
3. School of Automation, Northwestern Polytechnical University, Xi’an 710072, China;
4. School of Engineering, Vanderbilt University, TN 37235, USA

Online:2015-04-21 Published:2010-01-03

Abstract

Abstract:

Identifying influential nodes in complex networks is still an open issue. In this paper, a new comprehensive centrality measure is proposed based on the Dempster-Shafer evidence theory. The existing measures of degree centrality, betweenness centrality and closeness centrality are taken into consideration in the proposed method. Numerical examples are used to illustrate the effectiveness of the proposed method.

Key words: Dempster-Shafer evidence theory (D-S theory), belief function, complex networks, influential nodes, evidential centrality, comprehensive measure

Hongming Mo, Cai Gao, and Yong Deng. Evidential method to identify influential nodes in complex networks[J]. Journal of Systems Engineering and Electronics, doi: 10.1109/JSEE.2015.00044.

[1]	Yinghui YANG, Jianhua LI, Di SHEN, Mingli NAN, Qiong CUI. Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges [J]. Journal of Systems Engineering and Electronics, 2018, 29(3): 549-559.
[2]	Bin Chen, Zhixue Wang, and Chen Luo. Integrated evaluation approach for node importance of complex networks based on relative entropy [J]. Journal of Systems Engineering and Electronics, 2016, 27(6): 1219-1226.
[3]	Hongming Mo, Xi Lu, and Yong Deng. A generalized evidence distance [J]. Journal of Systems Engineering and Electronics, 2016, 27(2): 470-476.

Evidential method to identify influential nodes in complex networks

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