通信学报2024，Vol.45Issue(3)：258-269,12.DOI:10.11959/j.issn.1000-436x.2024052
基于模体结构和度信息的关键节点组识别
Identification of key node groups based on motif structure and degree information
摘要
Abstract
In order to explore the impact of higher-order structures with smaller scales on key node group mining prob-lems and with the goal of optimizing network propagation,a key node group recognition algorithm was proposed based on motif structure and degree information.Firstly,the influence of nodes was evaluated based on the motif structure,and the core nodes of the motif structure were excavated.Then,the VIKOR method was used to fuse it with degree infor-mation.Finally,the seed exclusion algorithm was used to exclude the neighbors of the seed nodes,effectively reducing the problem of influence overlap.Based on the SIR propagation model,six different undirected networks were selected for comparison with four benchmark algorithms.The experimental results show that the proposed algorithm performs better in terms of accuracy and stability.关键词
模体/关键节点组/影响力最大化Key words
motif/key node group/influence maximization分类
信息技术与安全科学引用本文复制引用
杨云云,张辽,于海龙,王力..基于模体结构和度信息的关键节点组识别[J].通信学报,2024,45(3):258-269,12.基金项目
国家自然科学基金资助项目(No.62006169) The National Natural Science Foundation of China(No.62006169) （No.62006169）
