Intelligence Eyewear Recommen-dation system

With the trend of digital transformation in the industry, more and more fashion industries search for a new channel to engage with their customers and promote their products simultaneously. Fashion recommender systems gain a surge of attention in rent years. In this paper, I present an eyewear recommender system, the project cooperated with PTTRNS.ai, that provides style-based personalization service. It is an intelligent recommender system that means data plays an essential role in the entire process. Therefore, I started exploring data that can contribute to the performance of the system, then designing structure interaction, and experience to collect all needed data. I also dived into style study, which contributes to providing harmonious matching in the beginning and collecting meaningful feedback to feed the intelligent model. Finally, an evaluation plan has been developed to assess User experience of the intelligent recommender that is suitable for a business-oriented system.