Multi-Order-Content-Based Adaptive Graph Attention Network for Graph Node Classification

Multi-Order-Content-Based Adaptive Graph Attention Network for Graph Node Classification

In graph-structured data, the node content contains rich information. Therefore, how to effectively utilize the content is crucial to improve the performance of graph convolutional networks (GCNs) on various analytical tasks. However, current GCNs do not fully utilize the content, especially multi-o...

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Bibliographic Details
Main Authors:	Yong Chen, Xiao-Zhu Xie, Wei Weng, Yi-Fan He
Format:	Article
Language:	English
Published:	MDPI AG 2023-05-01
Series:	Symmetry
Subjects:	symmetry graph neural network graph convolutional network graph attention network node classification
Online Access:	https://www.mdpi.com/2073-8994/15/5/1036

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