2 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation
Weizhi Zhang, Liangwei Yang, Zihe Song +4
Recommender systems (RecSys) are essential for online platforms, providing personalized suggestions to users within a vast sea of information. Self-supervised graph learning seeks…
Graph Neural Controlled Differential Equations For Collaborative Filtering
Ke Xu, Weizhi Zhang, Zihe Song +2
Graph Convolution Networks (GCNs) are widely considered state-of-the-art for recommendation systems. Several studies in the field of recommendation systems have attempted to apply…
Item Cluster-aware Prompt Learning for Session-based Recommendation
Wooseong Yang, Chen Wang, Zihe Song +2
Session-based recommendation (SBR) aims to capture dynamic user preferences by analyzing item sequences within individual sessions. However, most existing approaches focus mainly o…
Mixed Supervised Graph Contrastive Learning for Recommendation
Weizhi Zhang, Liangwei Yang, Zihe Song +4
Recommender systems (RecSys) play a vital role in online platforms, offering users personalized suggestions amidst vast information. Graph contrastive learning aims to learn from h…