This paper introduces a multi-model ontology-based
framework for semantic search of educational content in Elearning repository of courses, lectures, multimedia resources,
etc. This hybrid recommender system is driven by two types
of recommendations: content-based (domain ontology model) and
rule-based (learner’s interest-based and cluster-based). The domain ontology is used to represent the learning materials. In this
context, the ontology is composed by a hierarchy of concepts and
sub-concepts. Whereas, the learner’s ontology model represents
a subset of the domain ontology, and the cluster-based recommendations are added as additional semantic recommendations
to the model. Combining the content-based with the rule-based
provides the user with hybrid recommendations. All of them influenced the re-ranking of the retrieved documents with different
weights. Our proposed approach has been implemented on the
HyperManyMedia1 platform.