Adaptive hybrid recommender system of learning objects

Abstract:

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.

Año de publicación:

2016

Keywords:

• Calibration of recommenders
• Intelligent Recommender Systems
• Learning objects
• Learning style

Fuente:

scopus