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In this paper, we describe an integrated and working Elearning search system for retrieving personalized semantically enriched learning resources. Within this context, this work proposes an architecture divided into four layers: (1) Semantic Representation (knowledge representation), (2) Algorithms, which are the core engine of this study, (3) Personalization Interface to deal with information filtering, and (4) Dual representation of the semantic user profile. We use Cluster Analysis indoi:10.1109/icsc.2009.107 dblp:conf/semco/ZhuhadarNWR09 fatcat:yuk2axkmfrbgbh7vadjuatic5y