A centrality measure based on spectral optimization of modularity density
A centrality measure based on spectral optimization of modularity density作者机构：School of Computer Science and Engineering Xidian University Xi’an China College of Computer Xi’an University of Science and Technology Xi’an China
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2010年第53卷第9期
页 面：1727-1737页
核心收录：
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the National Natural Science Foundation of China(Grant Nos.60933009,60970065) the Ph.D Programs Foundation of Ministry of Education of China(Grant No.200807010013)
主 题：centrality modularity density centrality kernel matrix eigenspectrum
摘 要：Centrality analysis has been shown to be a valuable method for the structural analysis of complex *** is used to identify key elements within networks and to rank network elements such that experiments can be tailored to interesting *** this paper,we show that the optimization process of modularity density can be written in terms of the eigenspectrum of kernel *** on the eigenvectors belonging to the largest eigenvalue of kernel matrix,we present a new centrality measure that characterizes the contribution of each node to its assigned community in a network,called modularity density *** measure is illustrated and compared with the standard centrality measures by using respectively an artificial example and a classic network data *** statistical distribution of modularity density centrality is investigated by considering large computer generated graphs and two large networks from the real *** results show the significance of the proposed approach.
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