Advanced Learning Technologies, IEEE International Conference on (2007)
July 18, 2007 to July 20, 2007
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICALT.2007.63
Ming Che Lee , National Cheng Kung University, Taiwan
Kun Hua Tsai , National Cheng Kung University, Taiwan
Tung Cheng Hsieh , National Cheng Kung University, Taiwan
Ti Kai Chiu , National Cheng Kung University, Taiwan
Tzone I Wang , National Cheng Kung University, Taiwan
This paper presents a semantic-aware classification algorithm that can leverage the interoperability among semantically heterogeneous learning object repositories using different ontologies. The proposed algorithm is to map sharable learning objects, using meanings instead of just keyword matching, from heterogeneous repositories into a local knowledge base (an e-learning ontology). Significance of this research lies in the semantic inferring rules for learning objects classification as well as the full automatic processing and self-optimizing capability. This approach is sufficiently generic to be embedded into other e-learning platforms for semantic interoperability among learning object repositories. Focused on digital learning material and contrasted to other traditional classification technologies, the proposed approach has experimentally demonstrated significantly improvement in performance.
T. C. Hsieh, M. C. Lee, T. I. Wang, K. H. Tsai and T. K. Chiu, "An Ontological Approach for Semantic Learning Objects Interoperability," 2007 International Conference on Advanced Learning Technologies(ICALT), Niigata, 2007, pp. 222-226.