Catalyzing Social Interactions in Mixed Reality using ML Recommendation Systems

arXiv:2404.19095v1 Announce Type: cross
Abstract: We create an innovative mixed reality-first social recommendation model, utilizing features uniquely collected through mixed reality (MR) systems to promote social interaction, such as gaze recognition, proximity, noise level, congestion level, and conversational intensity. We further extend these models to include right-time features to deliver timely notifications. We measure performance metrics across various models by creating a new intersection of user features, MR features, and right-time features. We create four model types trained on different …

abstract arxiv congestion conversational create cs.hc cs.ir cs.lg cs.si features intensity interactions mixed mixed reality noise promote reality recognition recommendation recommendation model recommendation systems social systems through type