Abstract
Most of the Open Educational Resources are scattered around the Web, and not well described and structured so causing huge problems in their use, search, organization and management. We present a system which can collect and analyze domain-specific contents from massive online learning materials and publications, and automatically identify domain-specific knowledge terms and aggregate them into well-organized topics. The system helps learners who want to learn cutting-edge technology to effectively and efficiently locate appropriate online courses and learning materials using topic-specific recommendation. We further examines the system with real-world data and applications.
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Wang, J., Xiang, J., Uchino, K. (2015). Topic-Specific Recommendation for Open Education Resources. In: Li, F., Klamma, R., Laanpere, M., Zhang, J., Manjón, B., Lau, R. (eds) Advances in Web-Based Learning -- ICWL 2015. ICWL 2015. Lecture Notes in Computer Science(), vol 9412. Springer, Cham. https://doi.org/10.1007/978-3-319-25515-6_7
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DOI: https://doi.org/10.1007/978-3-319-25515-6_7
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