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Identifying critical edges in complex networks.
Yu, En-Yu; Chen, Duan-Bing; Zhao, Jun-Yan.
Afiliación
  • Yu EY; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
  • Chen DB; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China. dbchen@uestc.edu.cn.
  • Zhao JY; The Center for Digitized Culture and Media, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China. dbchen@uestc.edu.cn.
Sci Rep ; 8(1): 14469, 2018 Sep 27.
Article en En | MEDLINE | ID: mdl-30262804
ABSTRACT
The critical edges in complex networks are extraordinary edges which play more significant role than other edges on the structure and function of networks. The research on identifying critical edges in complex networks has attracted much attention because of its theoretical significance as well as wide range of applications. Considering the topological structure of networks and the ability to disseminate information, an edge ranking algorithm BCCMOD based on cliques and paths in networks is proposed in this report. The effectiveness of the proposed method is evaluated by SIR model, susceptibility index S and the size of giant component σ and compared with well-known existing metrics such as Jaccard coefficient, Bridgeness index, Betweenness centrality and Reachability index in nine real networks. Experimental results show that the proposed method outperforms these well-known methods in identifying critical edges both in network connectivity and spreading dynamic.

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2018 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2018 Tipo del documento: Article