Evaluation of Node Importance Based on Topological Potential in Weighted Complex Networks

被引：1

作者：

Sun Rui ^{[1
]}

Mu A-li ^{[1
]}

Li Lin ^{[1
]}

Zhong Mi ^{[1
]}

机构：

[1] Sichuan Univ, Sch Comp Sci, Chengdu 610064, Peoples R China

来源：

FOURTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2011): MACHINE VISION, IMAGE PROCESSING, AND PATTERN ANALYSIS | 2012年 / 8349卷

关键词：

weighted complex networks; node importance; topological potential; potential entropy; node quality; CENTRALITY;

D O I：

10.1117/12.920232

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The unweighted networks only reflect the connection type between nodes and the network topology characteristics, by contrast, the weighted networks could describe the strength of interaction between nodes. For this reason, the weighted networks will give a better understanding of the characteristics of real-world networks and the complicated features of complex systems. The evaluation of node importance is a very meaningful research in weighted complex networks. This paper analyze the characteristics of weighted complex network and consider the effects of edge weights for the evaluation of node importance, introduces the idea of data field in theoretical physics and establishes the evaluation model of node importance in weighted complex network. Through the theoretical and experimental analysis, it is proved that this method can evaluate the importance of node in weighted complex network in a fast and accurate way, which is significant both to theory and practice.

引用

页数：7

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