基于主成分分析的网络节点重要性指标贡献评价

doi:10.3969/j.issn.0372-2112.2019.02.015

电子学报 ›› 2019, Vol. 47 ›› Issue (2): 358-365.DOI: 10.3969/j.issn.0372-2112.2019.02.015

基于主成分分析的网络节点重要性指标贡献评价

胡钢¹, 徐翔², 张维明², 周鋆²

1. 安徽工业大学管理科学与工程学院, 安徽马鞍山 243032;
2. 国防科技大学信息系统工程重点实验室, 湖南长沙 410073

收稿日期:2018-07-02 修回日期:2018-08-09 出版日期:2019-02-25
- 作者简介:
- 胡钢男,1970年出生,甘肃天水人.博士后,副教授,主要研究方向为复杂网络系统建模仿真与均衡分析、多属性决策、供应链金融.E-mail:hug_2004@126.com;徐翔男,1993年出生,安徽滁州人.现为在读博士研究生,主要研究方向为复杂网络系统建模仿真与均衡分析、供应链网络仿真与应用.E-mail:18726008700@163.com
- 基金资助:
- 国家自然科学基金 (No.61672372，No.61472211）

Contribution Analysis for Assessing Node Importance Indices with Principal Component Analysis

HU Gang¹, XU Xiang², ZHANG Wei-ming², ZHOU Yun²

1. School of Management Science and Engineering, Anhui University of Technology, Maanshan, Anhui 243032, China;
2. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, Hunan 410073, China

Received:2018-07-02 Revised:2018-08-09 Online:2019-02-25 Published:2019-02-25
- Supported by:
- National Natural Science Foundation of China (No.61672372, No.61472211)

摘要/Abstract

摘要： 为研究不同网络节点重要性指标对网络中重要节点的影响程度，进而优选出较能体现网络重要节点性质的指标.本文基于主成分分析（Principal Component Analysis，简记PCA），选取七个节点重要性指标对网络重要性节点贡献率进行计算分析，同时选取了七种不同的网络进行实验，得到指标贡献率大小顺序，利用肯德尔系数对重要指标与其余指标进行相关性分析，得到不同指标之间的相关系数及相关系数大小的影响因素.本文为研究网络重要节点选择指标提供了一种思路，同时为研究不同节点间的相互关系提供了研究方法.

关键词: 主成分分析, 节点重要性, 贡献率, 肯德尔系数

Abstract: In network theory,it is interest to study the influences of different nodes on the key nodes in the network,and build or select the proper node importance index to model it.This paper selects seven node importance indices to calculate and analyze their contributions in nodes' importance evaluation with Principal Component Analysis.Seven empirical networks are used for experiments.Moreover,the order of different contributions of indices is obtained,and the correlation analysis between the most important index and the other indices is carried out using the Kendall coefficient,and factors affecting the correlation coefficient are also discussed.This paper provides a way to select the node importance index in the network,and the results could also be used for studying the relationships between different nodes.

Key words: principal component analysis, node importance index, contribution analysis, Kendall coefficient

中图分类号:

TP393

胡钢, 徐翔, 张维明, 等. 基于主成分分析的网络节点重要性指标贡献评价[J]. 电子学报, 2019, 47(2): 358-365.

HU Gang, XU Xiang, ZHANG Wei-ming, et al. Contribution Analysis for Assessing Node Importance Indices with Principal Component Analysis[J]. Acta Electronica Sinica, 2019, 47(2): 358-365.

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基于主成分分析的网络节点重要性指标贡献评价

Contribution Analysis for Assessing Node Importance Indices with Principal Component Analysis

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