Improving Enjoyment of Cultural Heritage Through Recommender Systems, Virtual Tour, and Digital Storytelling

The integration of Information and Communication Technologies (ICT) within the world of cultural heritage has the role of added value for its enhancement. In particular, improving the enjoyment of cultural Points of Interest by suggesting personalized routes allows for better interaction between users and the cultural site. To this end, this paper aims to introduce an architecture that, by employing Recommendation Systems integrated with the Situation Awareness paradigm, allows for the identification of personalized paths for users through the acquisition of data through smart sensors, which is then processed through the proposed approach, defined as a Multilevel Graph (MuG) approach. This aims to filter through the data’s context and ontological layers to its processing through the Bayesian network, which is identified through structural learning algorithms integrated with the domain’s semantic knowledge. The architecture also incorporates physical and virtual experiences, exploiting the advantages of virtual tours and involving users more by employing digital storytelling techniques. Testing of the proposed architecture based on the MuG approach took place through an offline experiment aimed at evaluating the accuracy of the approach used and an online experiment to test the validity of the designed architecture.