DAG: Dual Attention Graph Representation Learning for Node Classification
Siyi Lin,
Jie Hong,
Bo Lang
et al.
Abstract:Transformer-based graph neural networks have accomplished notable achievements by utilizing the self-attention mechanism for message passing in various domains. However, traditional methods overlook the diverse significance of intra-node representations, focusing solely on internode interactions. To overcome this limitation, we propose a DAG (Dual Attention Graph), a novel approach that integrates both intra-node and internode dynamics for node classification tasks. By considering the information exchange proc… Show more
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