Zusammenfassung
The main focus of this paper is to apply an ontologybased
approach for semantic learning object recommendation
towards personalized e-learning systems. Ontologies for
learner model, learning objects and semantic mapping rules
are proposed. The recommender can be able to provide
individually learning object by taking the learner preferences
and styles, which used to adjust or fine-tune in learning object
recommending process. In the proposed framework, we
demonstrated how the ontologies can be used to enable
machines to interpret and process learning resources in
recommendation system. The recommendation consists of four
steps: semantic mapping between learner and learning
objects, preference score calculation, learning object ranking
and recommending the learning object. As a result, a
personalized and most suitable learning object is
recommended to the learner.
Nutzer