SIHAN: Semantic-Instance Guided Hypergraph Attention Network With Dual-View Contrastive Learning for Heterogeneous Graph
Heterogeneous graphs are well-suited to modeling the diverse types of entities and their complex interactions in the real world. However, existing Heterogeneous Graph Neural Networks (HGNNs) are typically based on the binary message-passing framework, which struggles to explicitly and finely describe the higher-order s...