An Architecture Based on Recommender Systems and Context Awareness to Suggest Personalized Cultural Experiences

The enhancement of artistic and cultural heritage is a challenge for new technologies. In particular, enhancing users’ cultural experience makes it possible to attract more visitors, ensuring better interaction between visitors and cultural assets. This work aims to describe an architecture capable of enhancing the artistic and cultural heritage by suggesting personalized paths to users who will be able to take advantage of narratives elaborated with Digital Storytelling techniques that aim to engage users better. The heart of the architecture is the Context-Aware Recommender System (CARS) based on tensor factorization and hybrid techniques that allow the selection of POIs to be integrated within the suggested routes. The experimental phase aims to evaluate the accuracy and quality of the suggestions processed by the proposed CARS on the DePaulMovie dataset. The results obtained are satisfactory.