Using planning techniques in intelligent tutoring systems
International Journal of Man-Machine Studies
An epistemic operator for description logics
Artificial Intelligence
Course and exercise sequencing using metadata in adaptive hypermedia learning systems
Journal on Educational Resources in Computing (JERIC)
Instructional Use of Learning Objects
Instructional Use of Learning Objects
Reasoning with Expressive Description Logics: Theory and Practice
CADE-18 Proceedings of the 18th International Conference on Automated Deduction
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Reducing OWL entailment to description logic satisfiability
Web Semantics: Science, Services and Agents on the World Wide Web
Knowledge integration through semantic query rewriting
ACS'09 Proceedings of the 9th WSEAS international conference on Applied computer science
Design of a performance-oriented workplace e-learning system using ontology
Expert Systems with Applications: An International Journal
GMQL: A graphical multimedia query language
Knowledge-Based Systems
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Learning objects paradigm is widely adopted in e-learning environments. Learning objects management can be improved using semantic technologies from ontology engineering and the semantic web. In this article we use a semantic model of the repository to improve both learning objects retrieval and composition. The use of domain knowledge enables automatic reasoning and makes the system able to import new domain models and use them to interrogate the repository (Arrigoni Neri 2005). Learning objects composition is one of the main challenges in e-learning management systems and can be improved exploiting ontological reasoning. The building of a course can be carried out in two phases, in the first phase we compose concept level entities to obtain an outline of the course, then we fill the outline with actual resources from the repository. Both phases can use ontology-based models to capture specific domain knowledge (Arrigoni Neri 2006). In order to provide an intuitive and expressive ontology representation, we briefly propose a graphical syntax for the well-known ontology web language (OWL).