典型文献
A Novel Method Based on Node's Correlation to Evaluate Important Nodes in Complex Networks
文献摘要：
Finding the important nodes in complex networks by topological structure is of great significance to network invulnerability.Several centrality measures have been proposed recently to evaluate the performance of nodes based on their correlation,showing that the interaction between nodes has an influence on the importance of nodes.In this paper,a novel method based on node's distribution and global influence in complex networks is proposed.The nodes in the complex networks are classified according to the distance matrix;then the correlation coefficient between pairs of nodes is calculated.From the whole perspective in the network,the global similarity centrality(GSC)is proposed based on the relevance and the shortest distance between any two nodes.The effi-ciency,accuracy,and monotonicity of the proposed method are analyzed in two artificial datasets and eight real datasets of different sizes.Experimental results show that the performance of GSC method outperforms those current state-of-the-art algorithms.
文献关键词：
中图分类号：
作者姓名：
LU Pengli;DONG Chen;GUO Yuhong
作者机构：
School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China;School of Management,Shanghai University,Shanghai 200444,China;School of Mathematics and Statistics,Hexi University,Zhangye 734000,Gansu,China
文献出处：
引用格式：
[1]LU Pengli;DONG Chen;GUO Yuhong-.A Novel Method Based on Node's Correlation to Evaluate Important Nodes in Complex Networks)[J].上海交通大学学报（英文版）,2022(05):688-698
A类：
invulnerability
B类：
Novel,Method,Based,Correlation,Evaluate,Important,Nodes,Complex,Networks,Finding,important,nodes,complex,networks,by,topological,structure,great,significance,Several,centrality,measures,have,been,proposed,recently,evaluate,performance,their,correlation,showing,that,interaction,between,has,influence,importance,In,this,paper,novel,method,distribution,global,are,classified,according,distance,matrix,then,coefficient,pairs,calculated,From,whole,perspective,similarity,GSC,relevance,shortest,any,ciency,accuracy,monotonicity,analyzed,artificial,datasets,eight,real,different,sizes,Experimental,results,outperforms,those,current,state,algorithms
AB值：
0.551875
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机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
