4.6 Article

Identifying influential nodes in weighted networks based on evidence theory

期刊

出版社

ELSEVIER
DOI: 10.1016/j.physa.2013.01.054

关键词

Complex networks; Influential nodes; Weighted network; Dempster-Shafer theory of evidence

资金

  1. Chongqing Natural Science Foundation [CSCT, 2010BA2003]
  2. National Natural Science Foundation of China [60933006, 61174022]
  3. National High Technology Research and Development Program of China (863 Program) [2013AA013801]
  4. Fundamental Research Funds for the Central Universities [XDJK2012D009]
  5. Doctor Funding of Southwest University [SWU110021]
  6. China State Key Laboratory of Virtual Reality Technology and Systems

向作者/读者索取更多资源

The design of an effective ranking method to identify influential nodes is an important problem in the study of complex networks. In this paper, a new centrality measure is proposed based on the Dempster-Shafer evidence theory. The proposed measure trades off between the degree and strength of every node in a weighted network. The influences of both the degree and the strength of each node are represented by basic probability assignment (BPA). The proposed centrality measure is determined by the combination of these BPAs. Numerical examples are used to illustrate the effectiveness of the proposed method. (C) 2013 Elsevier B.V. All rights reserved.

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