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Huilin Chen

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Review Open access Sep 2026

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.

Huilin Chen, Zhi-Yong Cheng, Fan Liu et al. · 0 citations

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