Personalized AR Content and POI Recommendation in Mobile Cultural Heritage Systems Using Semantic Relatedness

This paper presents a mobile augmented reality (AR) system designed to enhance user experiences at cultural heritage (CH) sites by providing personalized content and points of interest (POI) recommendations. Applying semantic relatedness, we address the heterogeneity of CH POIs to improve personalization accuracy. Our system constructs a POI-based co-occurrence graph to model semantic relationships, enriching users' visited AR content items for better recommendations. The proposed method integrates content-filtering-based recommendations with this graph and recommends personalized POIs and AR content items. A user study demonstrated that our system outperforms conventional methods by 9.4% in recommendation precision and recall, significantly enhancing user engagement and attention focus during CH tours.