基于网络超链接信息熵的节点重要性序结构演化建模分析

doi:10.12263/DZXB.20211307

电子学报 ›› 2022, Vol. 50 ›› Issue (11): 2638-2644.DOI: 10.12263/DZXB.20211307

基于网络超链接信息熵的节点重要性序结构演化建模分析

胡钢¹, 牛琼¹, 许丽鹏¹, 卢志宇¹, 过秀成²

^1.安徽工业大学管理科学与工程学院, 安徽马鞍山 243032
^2.东南大学交通学院, 江苏南京 210096

收稿日期:2021-09-23 修回日期:2022-01-08 出版日期:2022-11-25
- 作者简介:
- 胡钢男, 1970年出生于甘肃省天水市;安徽工业大学管理科学与工程学院副教授, 硕士生导师; 研究方向: 多属性决策、复杂网络系统建模仿真与均衡分析.E-mail: hug_2004@126.com
  牛琼男, 1997年出生于安徽省亳州市;安徽工业大学在读硕士研究生, 主要研究方向为复杂网络系统建模仿真与均衡分析、多属性决策.E-mail: NiuQiongNQ@163.com
- 基金资助:
- 国家自然科学基金 (71772002); 安徽省自然科学基金 (2108085MG236); 安徽省高校自然科学研究项目 (KJ2021A0385); 安徽省高校研究生科学研究项目 (YJS20210356)

The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy

HU Gang¹, NIU Qiong¹, XU Li-peng¹, LU Zhi-yu¹, GUO Xiu-cheng²

^1.School of Management Science and Engineering，Anhui University of Technology，Maanshan，Anhui 243032，China
^2.School of Transportation，Southeast University，Nanjing，Jiangsu 210096，China

Received:2021-09-23 Revised:2022-01-08 Online:2022-11-25 Published:2022-11-19

摘要/Abstract

摘要：

动态复杂网络在时空演化过程中，网络节点重要性层内交互关系和层间耦合关系可以更为准确对时序网络节点序结构演化进行分析.本文提出基于网络超链接信息熵的节点重要性序结构演化模型.分析时序网络层内节点超链接信息熵重要性排序结果，得到时序网络节点相邻时间层与跨时间层节点重要性排序模型.节点超链接信息熵总结相邻时间层与跨时间层节点相似性耦合效应.通过SIR（Susceptible Infected Recovered）模型检验节点传播效率进行实证网络仿真，结果与经典时序网络模型相比，本文模型 $? K e n d a l l' s ? τ$ 值在各时间层均有提高，最高为11.310%.

关键词: 动态时序网络, 超链接信息熵, 节点重要性, 序结构, 层内相似, 层间耦合

Abstract:

In the time evolution of dynamic complex networks, the intra-layer interaction relationship and inter-layer coupling relationship of the importance of network nodes can be more accurately analyzed for the evolution of the node order structure of the time ordered networks. In this paper, a model of node importance order structure evolution based on network hyperlink information entropy is proposed. Through the results of the importance ranking of node hyperlink information entropy within the temporal network layer, the importance ranking model of nodes in the adjacent temporal layer and across temporal layers of the temporal network is analyzed. The entropy of node hyperlink information summarizes the coupling effect of similarity between adjacent temporal layers and inter-temporal layers. An empirical network simulation was conducted to check the node propagation efficiency by SIR(Susceptible Infected Recovered) model. Compared with the classical temporal network model, the $? K e n d a l l' s ? τ$ value of this model was improved in all time layers, with the highest value of 11.310%.

Key words: dynamic temporal networks, hyperlink information entropy, node importance, ordered structure, intralayer similarity, interlayer coupling

中图分类号:

TP393

胡钢, 牛琼, 许丽鹏, 卢志宇, 过秀成. 基于网络超链接信息熵的节点重要性序结构演化建模分析[J]. 电子学报, 2022, 50(11): 2638-2644.

HU Gang, NIU Qiong, XU Li-peng, LU Zhi-yu, GUO Xiu-cheng. The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy[J]. Acta Electronica Sinica, 2022, 50(11): 2638-2644.

图/表 5

图1 时序网络节点跨时间层耦合关系演化示意图

表1 实证网络基本统计特征

网络	N	C	E	During	T
Workspace	92	9827	755	2013.6.24-2013.7.3	10
Email-Eu-core	986	332334	24929	360d	12

图2 Workspace数据特征向量中心性与SIR排序结果的?Kendall's?τ值

图3 Email-Eu-core数据特征向量中心性与SIR排序结果的?Kendall's?τ值

图4 Email-Eu-core数据删除部分孤立节点后特征向量中心性与SIR排序结果的?Kendall's?τ值

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基于网络超链接信息熵的节点重要性序结构演化建模分析

The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy

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