Transferring Causal Mechanism over Meta-representations for Target-Unknown Cross-domain Recommendation.

The article explores non-overlapping cross-domain recommendation, addressing data sparsity issues in recommender systems by transferring interaction knowledge across domains without direct inter-domain correspondence. Topics include target-unknown cross-domain recommendation challenges, the proposed CMCDR framework leveraging causal mechanisms from meta-representations, and empirical validation demonstrating its effectiveness.