Attention-Based Recommendation On Graphs. (arXiv:2201.05499v1 [cs.IR])

Graph Neural Networks (GNN) have shown remarkable performance in different
tasks. However, there are a few studies about GNN on recommender systems. GCN
as a type of GNNs can extract high-quality embeddings for different entities in
a graph. In a collaborative filtering task, the core problem is to find out how
informative an entity would be for predicting the future behavior of a target
user. Using an attention mechanism, we can enable GCNs to do such an analysis
when the …

arxiv attention graphs