网络与信息安全学报2024，Vol.10Issue(1)：22-32,11.DOI:10.11959/j.issn.2096-109x.2024011
基于非回溯矩阵中心性的超图可靠性研究
Study on the reliability of hypergraphs based on non-backtracking matrix centrality
摘要
Abstract
In recent years,there has been widespread attention on hypergraphs as a research hotspot in network science.The unique structure of hypergraphs,which differs from traditional graphs,is characterized by hyperedges that can connect multiple nodes simultaneously,resulting in more complex and higher-order relationships.Effec-tively identifying important nodes and hyperedges in such network structures poses a key challenge.Eigenvector centrality,a common metric,has limitations in its application due to its locality when dealing with hub nodes with extremely high degree values in the network.To address this issue,the hypergraphs were transformed into their cor-responding line graphs,and non-backtracking matrix centrality was employed as a method to measure the im-portance of hyperedges.This approach demonstrated better uniformity and differentiation in assessing the im-portance of hyperedges.Furthermore,the application of both eigenvector centrality and non-backtracking matrix centrality in assessing the importance of nodes in hypergraphs was explored.Comparative analysis revealed that non-backtracking matrix centrality effectively distinguished the importance of nodes.This research encompassed theoretical analysis,model construction,and empirical studies on real-world data.To validate the proposed method and conclusion,six real-world hypergraphs were selected as experimental subjects.The application of these methods to these hypergraphs confirmed the effectiveness of non-backtracking matrix centrality in identifying important nodes and hyperedges.The findings of this research offer a fresh perspective and approach for identifying key ele-ments in hypergraphs,holding significant theoretical and practical implications for understanding and analyzing complex network systems.关键词
超图/特征向量中心性/非回溯矩阵中心性/向量中心性Key words
hypergraph/eigenvector centrality/non-backtracking matrix centrality/vector centrality分类
信息技术与安全科学引用本文复制引用
彭浩,钱程,赵丹丹,钟鸣,韩建民,谢紫伊,王伟..基于非回溯矩阵中心性的超图可靠性研究[J].网络与信息安全学报,2024,10(1):22-32,11.基金项目
国家自然科学基金(62074212,61902359,61702148) （62074212,61902359,61702148）
信息网络安全公安部重点实验室开放课题(C20607) （C20607）
重庆医科大学未来青年医学创新计划(W0150)The National Natural Science Foundation of China(62074212,61902359,61702148),The Open Project Program of the Key Laboratory of Information Network Security,Ministry of Public Security(C20607),The Program for Youth Innovation in Future Medicine,Chongqing Medical University(W0150) （W0150）
