Towards a semantic recommender system for cultural objects: Case study Draa-Tafilalet region

In the Big data era, a large number of functionalities and applications are created. The immediate consequence is the loss of time for the user due to the difficulty of accessing relevant information, and therefore a questioning of the usefulness of the services offered. Recommender system (RS) aims to help potential users by recommending the most suitable offers according to their profiles and preferences, RSs based on collaborative filtering, or those based on content or even hybrid filtering have shown interesting results to be explored for the resolution of the problems encountered. But some limits remain unresolved which are mainly related to the ability of these techniques to build a robust and complete system capable of forming a complete idea of the user profile and then recommend them the most suitable offers. Hence, the advantage of using semantic RSs based on data web and semantic web technologies, specifically the ontologies. This paper offers a comparative study of existing semantic RSs in the field of cultural heritage in order to extract a complete vision of a RS for the scientific cultural heritage of the region of Drâa-Tafilalet in Morocco.