标题:Temporal information gathering process for node ranking in time-varying networks
作者:Qu, Cunquan; Zhan, Xiuxiu; Wang, Guanghui; Wu, Jianliang; Zhang, Zi-ke
作者机构:[Qu, Cunquan; Wang, Guanghui; Wu, Jianliang] Shandong Univ, Sch Math, Jinan 250110, Shandong, Peoples R China.; [Zhan, Xiuxiu] Delft Univ Technol, I 更多
通讯作者:Zhan, XX
通讯作者地址:[Zhan, XX]Delft Univ Technol, Intelligent Syst, NL-2600 GA Delft, Netherlands.
来源:CHAOS
出版年:2019
卷:29
期:3
DOI:10.1063/1.5086059
摘要:Many systems are dynamic and time-varying in the real world. Discovering the vital nodes in temporal networks is more challenging than that in static networks. In this study, we proposed a temporal information gathering (TIG) process for temporal networks. The TIG-process, as a node's importance metric, can be used to do the node ranking. As a framework, the TIG-process can be applied to explore the impact of temporal information on the significance of the nodes. The key point of the TIG-process is that nodes' importance relies on the importance of its neighborhood. There are four variables: temporal information gathering depth n, temporal distance matrix D, initial information c, and weighting function f. We observed that the TIG-process can degenerate to classic metrics by a proper combination of these four variables. Furthermore, the fastest arrival distance based TIG-process (fad-tig) is performed optimally in quantifying nodes' efficiency and nodes' spreading influence. Moreover, for the fad-tig process, we can find an optimal gathering depth n that makes the TIG-process perform optimally when n is small. Published under license by AIP Publishing.
收录类别:SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062845419&doi=10.1063%2f1.5086059&partnerID=40&md5=3c711b399a171438aebaa2e4a18c288e
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