Domain-Based Recommendation and Retrieval of Relevant Materials in E-learning

Abstract

A good e-learning system should deliver relevant learning materials to learner at the most appropriate time and locations to facilitate learners' acquisition of knowledge and skills. In this paper, we propose domain-based recommendation and retrieval of relevant materials in e- learning. Since relevancy is often domain dependent. Materials that are highly related in one domain might be irrelevant in another domain, we group users by their domains. Based on the content, multiple sets of relevant documents, one for each chosen domain, are prepared. In a search scenario, search sites are selected by domain and search is performed on the chosen relevant sites only. To demonstrate our idea, we use Virtual Conference on Genomic and Bioinformatics as the test bed and develop a presentation video access platform. The implementation involves techniques in image and video processing, database management, programming, and multimedia learning materials presentation.

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Cite this paper

@article{Dong2008DomainBasedRA, title={Domain-Based Recommendation and Retrieval of Relevant Materials in E-learning}, author={Aijuan Dong and Baoying Wang}, journal={2008 IEEE International Workshop on Semantic Computing and Applications}, year={2008}, pages={103-108} }