Zhi-Yong Cheng

LLM-Driven Aspect-Based Semantic Alignment for Review-Based Recommendation

LLM-ASAR is proposed, a Large Language Model-driven framework for Aspect-based Semantic Alignment in Review-based Recommendation that explicitly aligns aspect-level review semantics with user–item interaction patterns and achieves significant accuracy improvements over state-of-the-art baselines.