Efficient Identification of Node Importance Based on Agglomeration in Cycle-Related Networks

Aysun Asena Kunt, Zeynep Nihan Berberler
{"title":"Efficient Identification of Node Importance Based on Agglomeration in Cycle-Related Networks","authors":"Aysun Asena Kunt, Zeynep Nihan Berberler","doi":"10.1142/s0129054120500379","DOIUrl":null,"url":null,"abstract":"The identification of node importance in complex networks is of theoretical and practical significance for improving network robustness and invulnerability. In this paper, the importance of each node is evaluated and important nodes are identified in cycles and related networks by node contraction method based on network agglomeration. This novel method considers both the degree and the position of the node for the identifying the importance of the node. The effectiveness and the feasibility of this method was also validated through experiments on different types of complex networks.","PeriodicalId":192109,"journal":{"name":"Int. J. Found. Comput. Sci.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Found. Comput. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0129054120500379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The identification of node importance in complex networks is of theoretical and practical significance for improving network robustness and invulnerability. In this paper, the importance of each node is evaluated and important nodes are identified in cycles and related networks by node contraction method based on network agglomeration. This novel method considers both the degree and the position of the node for the identifying the importance of the node. The effectiveness and the feasibility of this method was also validated through experiments on different types of complex networks.
基于环相关网络聚集的节点重要性高效识别
复杂网络中节点重要性的识别对于提高网络的鲁棒性和抗毁性具有重要的理论和现实意义。本文采用基于网络集聚的节点收缩方法,对循环及相关网络中各节点的重要性进行评估,识别出重要节点。该方法同时考虑节点的度和位置来识别节点的重要性。通过不同类型复杂网络的实验,验证了该方法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信