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复杂系统与复杂性科学  2025, Vol. 22 Issue (2): 113-119    DOI: 10.13306/j.1672-3813.2025.02.014
  复杂网络 本期目录 | 过刊浏览 | 高级检索 |
基于图注意力机制的复杂网络关键节点识别
张明磊a, 宋玉蓉b, 曲鸿博a
南京邮电大学 a.计算机学院、软件学院、网络空间安全学院; b.自动化学院、人工智能学院,南京 210023
Attention Mechanism-based Vital Nodes Identification in Complex Networks
ZHANG Mingleia, SONG Yurongb, QU Hongboa
a. School of Computer Science; b. College of Automation and College of Artificial Intelligence, Nanjing University of Post and Telecommunications, Nanjing 210023, China
全文: PDF(2730 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 为利用图注意力机制解决复杂网络中的关键节点识别问题,综合考虑节点传播力和结构影响力,在生成网络上构建训练标签,通过图注意力网络模型学习节点重要性。实验证明该算法在影响最大化和免疫隔离两个关键任务中表现出色。
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张明磊
宋玉蓉
曲鸿博
关键词 关键节点识别复杂网络影响力最大化病毒传播    
Abstract:This study aims to address the problem of vital nodes identification in complex networks using graph attention mechanism. This paper integrates both node′s virus transmissibility and structural impact, constructing training labels on the generated network to learn node importance through a graph attention network model. Experimental results demonstrate the excellence of this algorithm in two critical tasks: influence maximization and immune isolation.
Key wordsvital nodes identification    complex networks    influence maximization    virus transmission
收稿日期: 2023-09-18      出版日期: 2025-06-03
ZTFLH:  O157.5  
基金资助:国家自然科学基金(61672298);江苏高校哲学社会科学研究重点项目(2018SJZDI142)
通讯作者: 宋玉蓉(1971),女,河南扶沟人,博士,教授,主要研究方向为复杂网络传播动力学、信息安全。   
作者简介: 张明磊(1999),男,江苏南京人,硕士研究生,主要研究方向为复杂网络中关键节点识别。
引用本文:   
张明磊, 宋玉蓉, 曲鸿博. 基于图注意力机制的复杂网络关键节点识别[J]. 复杂系统与复杂性科学, 2025, 22(2): 113-119.
ZHANG Minglei, SONG Yurong, QU Hongbo. Attention Mechanism-based Vital Nodes Identification in Complex Networks[J]. Complex Systems and Complexity Science, 2025, 22(2): 113-119.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2025.02.014      或      https://fzkx.qdu.edu.cn/CN/Y2025/V22/I2/113
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