PAI-BPR：基于属性解释的个性化服装推荐方案
PAI-BPR: Personalized Outfit Recommendation Scheme with Attribute-wise Interpretability
摘要：
时尚是人类经验的重要组成部分。面试、会议、婚礼等活动往往以服装风格为基础。时尚产业的兴起及其对社会影响的影响使得服装的兼容性成为一种需求。因此，需要一个服装兼容性模型来帮助人们推荐服装。然而，由于兼容性的高度主观性，有必要考虑个性化。我们的论文设计了一个属性明智的可解释的兼容性计划与个人偏好建模，捕捉用户项目的互动，以及一般的项目项目的互动。我们的工作解决了服装搭配的解释性问题，通过定位时尚项目之间的不协调和和谐的属性。在IQON 3000（一个公开的真实世界数据集）上的大量实验结果验证了该模型的有效性。
英文摘要：
Fashion is an important part of human experience. Events such as interviews, meetings, marriages, etc. are often based on clothing styles. The rise in the fashion industry and its effect on social influencing have made outfit compatibility a need. Thus, it necessitates an outfit compatibility model to aid people in clothing recommendation. However, due to the highly subjective nature of compatibility, it is necessary to account for personalization. Our paper devises an attribute-wise interpretable compatibility scheme with personal preference modelling which captures user-item interaction along with general item-item interaction. Our work solves the problem of interpretability in clothing matching by locating the discordant and harmonious attributes between fashion items. Extensive experiment results on IQON3000, a publicly available real-world dataset, verify the effectiveness of the proposed model.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
