A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Ontological representation of learning objects: building interoperable vocabulary and structures
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Ontological interoperability of learning objects: a hybrid graphical-neural approach
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
LESSON: A system for lecture notes searching and sharing over Internet
Journal of Systems and Software
Knowledge discovery through composited visualization, navigation and retrieval
DS'05 Proceedings of the 8th international conference on Discovery Science
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Ontologies enable learning objects sharing and reuse in a contextual learning environment and provide better search and navigation of learning objects. Ontologies add semantics to content components, which provide context to learning objects. This paper presents the use of Formal Concept Analysis (FCA) to structure knowledge ontologically and the Self-Organizing Map (SOM) to reduce the problem size. To gain better visualization of the intrinsic relationship between ontological concepts, k-means clustering is applied on the clustered SOM.