Creating usage context-based object similarities to boost recommender systems in technology enhanced learning

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new similarity measure to enhance existing recommendation approaches for the use in technology enhanced learning.