User Activity Monitoring and Personalized Recommendations for Enhancing the VR Shopping Experience

Artificial Intelligence (AI) has had a significant impact on the e-commerce sector since its inception, enabling major retailers to gain a competitive edge. Through its application, these enterprises have been able to analyze data collected from user activity on their websites, subsequently crafting user profiles and identifying potential products that align with their preferences. In the forthcoming years, Virtual Reality (VR) is anticipated to emerge as a transformative advancement in human-computer interaction within the e-commerce domain. Therefore, it is crucial to incorporate AI within VR-developed environments to monitor user interactions therein to construct accurate user profiles. In this paper, we propose the definition and collection of four key actions that users can perform in VR Shopping environments. The activities we are able to register are tied to the current VR technology capabilities. These are further used to build user profiles and provide recommendations tailored to each user. Moreover, the algorithm built for product recommendation is detailed, as well as an evaluation of such recommendation system performed with a custom dataset of categorized products.