Self-supervised community detection in multiplex networks with graph convolutional autoencoder

Community detection in multiplex networks has received considerable attention in recent years. However, existing methods that combine graph embedding and downstream tasks still face two challenges. The first is how to fully explore the correlation among the layers in the multiplex networks, and the...

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Vydané v:	Proceedings of the ... International Conference on Computer Supported Cooperative Work in Design (Online) s. 1378 - 1383
Hlavní autori:	Liu, Xingyu, Cheng, Junwei, Cheng, Hao, He, Chaobo, Chen, Qimai, Guan, Quanlong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 24.05.2023
Predmet:	Community detection Computational modeling Correlation Federated learning Graph convolutional autoencoder Graph neural networks Multiplex networks Multiplexing Mutual information Self-supervised learning Task analysis
ISSN:	2768-1904
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