Collaborative Decision-Reinforced Self-Supervision for Attributed Graph Clustering

Attributed graph clustering aims to partition nodes of a graph structure into different groups. Recent works usually use variational graph autoencoder (VGAE) to make the node representations obey a specific distribution. Although they have shown promising results, how to introduce supervised informa...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 34; číslo 12; s. 10851 - 10863
Hlavní autori:	Zhu, Pengfei, Li, Jialu, Wang, Yu, Xiao, Bin, Zhao, Shuai, Hu, Qinghua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.12.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Attributed graph clustering (AGC) Automatic generation control Classification Clustering Collaboration collaborative training Convolutional neural networks Decisions Graphical representations Labels Learning Machine learning Nodes Representation learning self-supervised learning Sorting Supervision Task analysis Training variational graph autoencoder (VGAE)
ISSN:	2162-237X, 2162-2388, 2162-2388
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