A Novel Position-based VR Online Shopping Recommendation System based on Optimized Collaborative Filtering Algorithm

This paper proposes a VR supermarket with an intelligent recommendation. It consists of three parts: VR supermarket, recommendation system, and database. The VR supermarket provides a 360-degree virtual environment for users to move and interact in the virtual environment through VR devices. The recommendation system will make recommendations to the target users based on the data in the database. The intelligent recommendation system is developed based on item similarity (ICF), which solves the cold start problem of ICF. This allows VR supermarkets to present real-time recommendations in any situation. The VR supermarket not only makes up for the lack of user perception of item attributes in traditional online shopping system but also improve user shopping efficiency through an intelligent recommendation system. The application can be extended to enterprise-level systems and can add behavioral and voice interaction with NPC, adding new possibilities for users to do VR shopping at home.