论文标题
PAI-BPR：具有属性可解释性的个性化服装推荐计划
PAI-BPR: Personalized Outfit Recommendation Scheme with Attribute-wise Interpretability
论文作者
论文摘要
时尚是人类经验的重要组成部分。访谈，会议，婚姻等活动通常基于服装风格。时装界的增长及其对社会影响力的影响使服装兼容性成为必要性。因此，它需要一个服装兼容模型来帮助人们进行服装建议。但是，由于兼容性的高度主观性质，有必要考虑个性化。我们的论文通过个人喜好建模设计了属性的可解释兼容性方案，该模型捕获了用户 - 项目的交互以及一般项目项目的交互。我们的作品通过找到时尚物品之间的不和谐和和谐属性来解决服装匹配中的可解释性问题。 IQON3000（一种公开可用的现实世界数据集）的广泛实验结果验证了所提出的模型的有效性。
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.
