Aligning Ontologies to Bring Semantics to Learning Object Search

Within the educational context, researchers have focused on applying agent and ontology-based technologies to improve the processes of localization, retrieval, cataloging, and reuse of learning objects. This scenario highlights semantic heterogeneity issues, creating an excellent opportunity to evaluate, and explore ontology alignment techniques able to provide semantic integration between different ontologies. This work presents the MSSearch service, which combines state of the art agent and ontology-based technologies, with advanced alignment techniques to provide a semantic search service for a learning object repository. MSSearch was tested with a base of more than 11.000 learning object, answering queries in real-time. The quality of the answers were checked by educational experts and considered very satisfactory, when compared against similar queries made with the standard search engine of a public repository of learning objects, containing a similar set of learning objects.