Ying Guan

CGCLER: Causality-Enhanced Graph Contrastive Learning for Explainable Recommendation

Explainable recommendation has been conceptualized as a joint ranking task encompassing both items and explanations within contemporary recommender system research. The modeling of user–item–explanation triplets can be effectively facilitated by Graph Neural Networks (GNNs) due t...