Purchase Reason and Post-Purchase Experience Dataset

本研究首次提出了购买原因解释任务，并基于用户评论开发了一个高质量的个性化解释数据集，包含购买原因和购买后体验的文本解释。该数据集由大型语言模型（LLM）生成，通过区分购买原因和购买后体验，提供个性化解释。数据集应用于推荐系统的个性化解释生成任务，旨在提高用户对推荐系统的信任和理解。This study proposes the purchase reason explanation task for the first time. A high-quality personalized explanation dataset is developed based on user reviews, which contains textual explanations for both purchase reasons and post-purchase experiences. Generated by Large Language Models (LLMs), the dataset delivers personalized explanations by differentiating between purchase reasons and post-purchase experiences. This dataset is applied to the personalized explanation generation task in recommendation systems, aiming to enhance users' trust in and comprehension of recommendation systems.