A Hybrid Recommender System for Cultural Heritage Promotion

Abstract

Assisting users during their cultural trips is paramount in promoting the heritage of a territory. Recommender Systems offer the automatic tools to guide users in their decision process, by maximizing the adherence of the proposed contents with the particular preferences of every single user. However, traditional recommendation paradigms suffer from several drawbacks which are exacerbated in Cultural Heritage scenarios, due to the extremely wide range of users behaviors, which may also depend on their different educational backgrounds. In this paper, we propose a Hybrid recommender system which combines the four most common recommendation paradigms, namely collaborative filtering, popularity-, knowledge-, and content-based, according to different hybridization strategies. Experimental evaluation shows the versatility of the hybrid recommender with respect to the other paradigms adopted individually.