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

HU Gang; NIU Qiong; XU Li-peng; LU Zhi-yu; GUO Xiu-cheng

doi:10.12263/DZXB.20211307

您当前的位置：

首页 >

文章列表页 >

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

PAPERS | 更新时间：2025-12-08

- The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy
- ACTA ELECTRONICA SINICA Vol. 50, Issue 11, Pages: 2638-2644(2022)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20211307
  CLC： TP393
- Received：23 September 2021，
  
  Revised：2022-01-08，
  
  Published：25 November 2022
- 稿件说明：
移动端阅览
胡钢,牛琼,许丽鹏等.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,et al.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.
胡钢,牛琼,许丽鹏等.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. DOI： 10.12263/DZXB.20211307.

HU Gang,NIU Qiong,XU Li-peng,et al.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. DOI： 10.12263/DZXB.20211307.

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

http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=44119532&type=

http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=44119530&type=

15.49400043

2.70933342

值在各时间层均有提高，最高为11.310%.

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

http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=44119536&type=

http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=44119534&type=

15.49400043

2.70933342

value of this model was improved in all time layers

with the highest value of 11.310%.

关键词

Keywords

references

纪秋磊 , 梁伟 , 傅伯杰 , 等 . 基于Google Earth Engine与复杂网络的黄河流域土地利用/覆被变化分析 [J]. 生态学报 , 2021 , 42 ( 06 ): 1 ‑ 14 .

JI Qiu‑lei , LIANG Wei , FU Bo‑jie , et al . Land use/cover change in the Yellow River Basin beaed on Google Earth Engine and complex network [J]. Acta Ecologica Sinica , 2021 , 42 ( 06 ): 1 ‑ 14 . (in Chinese)

刘慧 , 王炳珺 , 陆君安 , 等 . 复杂网络牵制控制优化选点算法及节点组重要性排序 [J]. 物理学报 , 2021 , 70 ( 05 ): 284 ‑ 294 .

LIU Hui , WANG Bing‑jun , LU Jun‑an , et al . Node‑set importance and optimization algorithm of nodes selection in complex networks based on pinning control [J]. Chinese Journal of Physics , 2021 , 70 ( 05 ): 284 ‑ 294 . (in Chinese)

CHENFENG X , SONGHUA H , MOFENG Y , et al . Mobile device data reveal the dynamics in a positive relationship between human mobility and COVID‑19 infections [J]. Proceedings of the National Academy of Sciences , 2020 , 117 ( 44 ): 2 7087‑ 27089 .

YABE T , TSUBOUCHI K , FUJIWARA N , et al . Non‑compulsory measures sufficiently reduced human mobility in Tokyo during the COVID‑19 epidemic [J]. Scientific Reports , 2020 , 10 ( 1 ): 1 ‑ 9 .

刘金平 , 何捷舟 , 马天雨 , 等 . 基于KELM选择性集成的复杂网络环境入侵检测 [J]. 电子学报 , 2019 , 47 ( 5 ): 1070 ‑ 1078 .

LIU Jin‑ping , HE Jie‑zhou , MA Tian‑yu , et al . Selective ensemble of KELM‑Based complex network intrusion detection [J]. Acta Electronica Sinica , 2019 , 47 ( 5 ): 1070 ‑ 1078 . (in Chinese)

BONACICH P . Factoring and weighting approaches to status scores and clique identification [J]. Journal of Mathematical Sociology , 2010 , 2 ( 1 ): 113 .

Freeman L C . A set of measures of centrality based on betweenness [J]. Sociometry , 1977 , 40 ( 1 ): 35 ‑ 41 .

SABIDUSSI G . The centrality index of a graph [J]. Psychometrika , 1966 , 31 ( 4 ): 581 ‑ 603 .

BORGATTI S P . Centrality and network flow [J]. Social Networks , 2005 , 27 ( 1 ): 55 ‑ 71 .

ZELEN S M . Rethinking centrality: methods and examples [J]. Social Networks , 1989 , 11 ( 1 ): 1 ‑ 37 .

曹玖新 , 董丹 , 徐顺 , 等 . 一种基于 k ‑核的社会网络影响最大化算法 [J]. 计算机学报 , 2015 , 38 ( 02 ): 238 ‑ 248 .

CAO Jiu‑xin , DONG Dan , XU Shun , et al . A k ‑core based algorithm for influence maximization in social networks [J]. Chinese Journal of Computers , 2015 , 38 ( 02 ): 238 ‑ 248 . (in Chinese)

LIU Y , TANG M , ZHOU T , et al . Identify influential spreaders in complex networks, the role of neighborhood [J]. Physica A Statistical Mechanics & Its Applications , 2016 , 452 ( 12 ): 289 ‑ 298 .

LORRAIN F , WHITE H C . Structural equivalence of individuals in social networks [J]. Social Networks , 1977 , 1 ( 1 ): 67 ‑ 98 .

ADAMIC L A , ADAR E . Friends and neighbors on the Web [J]. Social Networks , 2003 , 25 ( 3 ): 211 ‑ 230 .

ZHOU T , LÜ L , ZHANG Y C . Predicting missing links via local information [J]. European Physical Journal B , 2009 , 71 ( 4 ): 623 ‑ 630 .

TAYLOR D , MYERS S A , CLAUSET A , et al . Eigenvector‑based centrality measures for temporal networks [J]. Multiscale Modeling & Simulation , 2017 , 15 ( 1 ): 537 ‑ 574 .

杨剑楠 , 刘建国 , 郭强 . 基于层间相似性的时序网络节点重要性研究 [J]. 物理学报 , 2018 , 67 ( 04 ): 279 ‑ 286 .

YANG Jian‑nan , LIU Jian‑guo , GUO Qiang . Node importance idenfication for temporal network based on inter‑layer similarity [J]. Chinese Journal of Physics , 2018 , 67 ( 04 ): 279 ‑ 286 . (in Chinese)

胡钢 , 许丽鹏 , 徐翔 . 基于时序网络层间同构率动态演化的重要节点辨识 [J]. 物理学报 , 2021 , 70 ( 10 ): 355 ‑ 366 .

HU Gang , XU Li‑peng , XU Xiang . Identification of important nodes based on dynamic evolution of inter‑layer isomorphism rate in temporal networks [J]. Chinese Journal of Physics , 2021 , 70 ( 10 ): 355 ‑ 366 . (in Chinese)

胡钢 , 高浩 , 徐翔 . 基于多属性偏好信息集结的复杂网络重要节点辨识 [J]. 浙江理工大学学报 , 2019 , 041 ( 004 ): 482 ‑ 488 .

HU Gang , GAO Hao , XU Xiang . Identify important nodes in complex network based on aggregation of multi ‑attribute preference information [J]. Journal of Zhejiang Sci‑Tech University , 2019 , 041 ( 004 ): 482 ‑ 488 . (in Chinese)

GÉNOIS M , BARRAT A . Can co‑location be used as a proxy for face‑to‑face contacts? [J]. EPJ Data Science , 2018 , 7 ( 1 ): 11 ‑ 29 .

PARANJAPE A , BENSON A R , LESKOVEC J . Motifs in Temporal Networks [M]. New York : Association Computing Machinery , 2017 : 601 ‑ 610 .

CASTELLANO C , PASTOR‑SATORRAS R . Thresholds for epidemic spreading in networks [J]. Physical Review Letters , 2010 , 105 ( 21 ): 218701 ‑ 218705 .

BORRONI C G . A new rank correlation measure [J]. Statistical Papers , 2013 , 54 ( 2 ): 255 ‑ 270 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Evaluation Method for Node Importance in Communication Network Based on Mutual Information

Related Author

Gang HU

Qiong NIU

Li-peng XU

Zhi-yu LU

Xiu-cheng GUO

MA Run-nian

WANG Ban

WANG Gang

Related Institution

School of Management Science and Engineering， Anhui University of Technology， Maanshan

School of Transportation， Southeast University

Information and Navigation Institute, Air Force Engineering University

Department of Physics and Electronic Information Engineering, Wenzhou University

Unit 95007 of PLA

⁰