Enhancing educational-material retrieval using authored-lesson metadata
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
iLOG: a framework for automatic annotation of learning objects with empirical usage metadata
International Journal of Artificial Intelligence in Education
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Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as "learning objective"', "related concept", etc. Manually expressing such metadata is a time consuming and expensive task.. Here we present an approach based on a probabilistic model, which through the automatic classification of learning resources on a given taxonomic organization of the knowledge, allows to associate ontological metadata to the learning resources.