August 12, 2024Open Access

Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation

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EXP3RT improves rating prediction accuracy through personalized preference reasoning and detailed explanations.
Key metrics include enhanced rating predictions and top-k candidate item reranking performance.
The approach uses large language models to extract and summarize user and item review information effectively for recommendations. It also transforms subjective preferences into user profiles.

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Review-driven approach enhances rating predictions and explainability in recommendation systems.

Kim et al. (2024) studied this question.

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