Multi-masks and Bi-spaces Reconstruction based Single-Layer Auto-encoder for Heterogeneous Graph Representation Learning

Generative self-supervised learning (SSL) for heterogeneous graph representation has drawn increasing attention due to its powerful capability of capturing rich structural and semantic information without relying on labeled information. However, the multi-layer network structure with multiple attent...

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Veröffentlicht in:	Proceedings of ... International Joint Conference on Neural Networks S. 1 - 9
Hauptverfasser:	Zhang, Pei, Zhou, Lihua, Wang, Lizhen, Chen, Hongmei, Xiao, Qing
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 30.06.2024
Schlagworte:	Attention mechanisms heterogeneous graph representation learning masked auto-encoder Neural networks Representation learning Self-supervised learning Semantics
ISSN:	2161-4407
Online-Zugang:	Volltext
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