Abstract:
In this paper, we present an approach that uses cluster analysis techniques to extend the ontology of an E-learning domain. This approach is significantly different from any current information retrieval systems, it uses a global ontology model that represents the whole E-learning domain combined with clusters’ centroids vocabularies (terms) to extend the core ontology model. The most important advantage of clustering from the personalization perspective is that the clusters are later used as automatically constructed labels for each user profile. Hence, depending on the document collection and its evolution, both the user profiles and their underlying ontology labels are allowed to change or evolve accordingly. Our proposed approach has been implemented on the HyperMany-Media1 platform at Western Kentucky University, USA.
