Baoyin Liu

Multi-graph Fusion Cross-model Contrastive Learning for Recommendation

Knowledge Graph (KG)-supported Graph Neural Network models are becoming crucial in recommendation systems due to their ability to mitigate the data sparsity challenge. However, these models remain suboptimal because they overlook the representation differences between the inherent user-item Bipartit