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Automatic classification of teaching and learning materials based on standard education classification schemes
Date
2008
Abstract
With the significant growth in available electronic education materials such as syllabus documents and lecture notes on the Internet and intranets there is a need for developing efficient indexing/categorizing mechanisms to organize such E-documents in institutional repositories. In this paper we describe our approach for automatic classification of syllabus documents in the national Irish syllabus repository. The classifier software component is based on the well-known naïve Bayes classification algorithm. We have also studied the application of a web corpus in training an unsupervised classifier which eliminates the need for manual classification of a training set required in standard classifications systems
Supervisor
Description
peer-reviewed
Publisher
Citation
Cranfield Multi-Strand Conference (CMC);