Sharp estimates for the personalized Multiplex PageRank

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:330

Article

Pedroche, Francisco¹  Garcia, Esther^2,3  Romance, Miguel^2,3  Criado, Regino^2,3 

[1] Univ Politecn Valencia, Inst Matemat Multidisciplinaria, Cami Vera S-N, E-46022 Valencia, Spain

[2] ESCET Univ Rey Juan Carlos, Dept Matemat Aplicada Ciencia & Ingn Mat Tecnol E, C Tulipan S-N, Mostoles 28933, Madrid, Spain

[3] Univ Politecn Madrid, Ctr Tecnol Biomed, Pozuelo De Alarcon 289223, Madrid, Spain

关键词: PageRank;    Centrality measures;    Multiplex networks;   

DOI  :  10.1016/j.cam.2017.02.013

来源: Elsevier

【 摘 要 】

PageRank can be understood as the stationary distribution of a Markov chain that occurs in a two-layer network with the same set of nodes in both layers: the physical layer and the teleportation layer. In this paper we present some bounds for the extension of this two-layer approach to Multiplex networks, establishing sharp estimates for this Multiplex PageRank and locating the possible values of the personalized PageRank for each node of a network. Several examples are shown to compare the values obtained for both algorithms, the classic and the two-layer PageRank. (C) 2017 Elsevier B.V. All rights reserved.

【 授权许可】

Free