郑州大学学报（理学版）2024，Vol.56Issue(2)：59-65,7.DOI:10.13705/j.issn.1671-6841.2022251
基于多指标交互的加权时序网络节点重要性
Importance of Weighted Temporal Network Nodes Based on the Multi-index Interaction
摘要
Abstract
The evaluation of essential nodes in temporal networks was a hot topic in social networks.It was widely used in virus transmission,information mining and so on.Although the current algorithms considered the influence of neighbour information on nodes,they only focused on whether nodes had rela-tionships without fully considering the link strength.A new intra-layer adjacency matrix was proposed to solve the problem by considering the node-link power from the time level.At the same time,a multi-in-dex interaction algorithm was used to measure the coupling relationship between layers by considering the neighbours of nodes themselves and the common neighbours of cross-layer nodes comprehensively.Sec-ondly,the weighted super-adjacency model(WSAM)was constructed on this basis.Finally,the impor-tance of nodes in the temporal network was evaluated by calculating the eigenvector centrality of each node in the temporal network.Experimental results showed that the TWCR algorithm outperformed SAM,SSAM and WPA regarding the maximum connected component,network performance and fault tolerance.关键词
多层网络/加权时序网络/节点重要性/多指标交互指数/最大连通分量Key words
multi-layer network/weighted temporal network/node importance/multi-index interaction index/largest connected component分类
信息技术与安全科学引用本文复制引用
杨晔彬,姜久雷,邹鹏..基于多指标交互的加权时序网络节点重要性[J].郑州大学学报（理学版）,2024,56(2):59-65,7.基金项目
国家自然科学基金项目(6172002). （6172002）
