A CBR Approach for e-Learning Content Categorization and Retrieval



Reuse and sharing of e-Learning contents is important for
companies that depend on this type of technology for employee formation.
But classification of e-Learning contents depends on the use of a
consistent vocabulary, so that teachers can find relevant contents for the
courses and materials that they are developing. Semi-automatic classification
is an approach that helps content developers to use the same or
similar classification terms, and at the same time facilitates the classification
task of the developers. This paper presents an approach to semiautomated
classification of e-Learning contents based on Textual Case-
Based Reasoning. We describe how contents are represented as cases and
how the extraction of classification topics is made. We also describe the
indexing and retrieval mechanisms, which are validated with experimental


CBR for Natural Language Processing

Related Project

PEGECEL- Personalização e Gestão de Conteúdos eLearning


EPIA 2007 - Portuguese Conference on Artificial Intelligence., December 2007

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