Adaptive hybrid recommender system of learning objects
José Aguilar, Omar Portilla, Eduard Puerto · 2016
This paper presents the general architecture of an adaptive recommender system of learning objects, whose recommendations combine three distinct aspects: contents, collaboration and knowledge. The recommender system is implemented like a semantic web service, designed with the framework FODAS-WS, which allows the specification of computational systems using ontologies, using the ODA (Ontology Driven Architecture) paradigm.