计算机应用研究2024，Vol.41Issue(10)：2926-2931,6.DOI:10.19734/j.issn.1001-3695.2024.03.0056
AGCFN:基于图神经网络多层网络社团检测模型
AGCFN:multiplex network community detection model based on graph neural network
摘要
Abstract
Multiplex network community detection methods based on graph neural network face two main challenges.Firstly,how to effectively utilize the node content information of multiplex network;and secondly,how to effectively utilize the interlayer relationships in multiplex networks.Therefore,this paper proposed the multiplex network community detection model AGCFN.Firstly,the autoencoder independently extracted the node content information of each network layer and passed the extracted node content information to the graph autoencoder for fusing the node content information of the current network layer with the topology information through the transfer operator to obtain the representation of each node of the current network layer,which made full use of the node content information of the network and the topology information of the network.The modularity maxi-mization module and graph decoder optimized the obtained node representation.Secondly,the multilayer information fusion module fused the node representations extracted from each network layer to obtain a comprehensive representation of each node.Finally,the model under went training,and it achieved community detection results through a self-training mechanism.Comparison with six models on three datasets demonstrate improvements in both ACC and NMI evaluation metrics,thereby va-lidating the effectiveness of AGCFN.关键词
多层网络/社团检测/图神经网络/自编码器/自监督学习Key words
multiplex network/community detection/graph neural network/autoencoder/self-supervised learning分类
信息技术与安全科学引用本文复制引用
陈龙,张振宇,李晓明,白宏鹏..AGCFN:基于图神经网络多层网络社团检测模型[J].计算机应用研究,2024,41(10):2926-2931,6.基金项目
国家自然科学基金资助项目(62272311) （62272311）
国家重点研发计划资助项目(2018YFC0831005) （2018YFC0831005）
中国天津经济技术开发区科技支撑计划资助项目(STCKJ2020-WRJ) （STCKJ2020-WRJ）
中国新疆建设兵团第十二师财务科技项目(SR202103) （SR202103）
