Abstract
This paper proposes the new method which adopts the knowledge-based reasoning algorithms and collaborative filtering to create an e-learning material recommendation system. Major problems in recommendation system (RS) will be considered, including data preprocess, feature extraction, combination of knowledge-based reasoning and collaborative filtering algorithms, method of forming a weighted hybrid RS for better prediction. The experimental results show that our proposed method can achieve better prediction accuracy when comparing to rule-based reasoning (RBR), case-based reasoning (CBR), and Matrix Factorization (MF).
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Acknowledgments
This research is the output of the project “Hybrid collaborative filtering for learning materials recommendation in e-learning” under grant number D2016-06 which belongs to University of Information Technology - Vietnam National University HoChiMinh City.
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Do, P., Nguyen, K., Vu, T.N., Dung, T.N., Le, T.D. (2017). Integrating Knowledge-Based Reasoning Algorithms and Collaborative Filtering into E-Learning Material Recommendation System. In: Dang, T., Wagner, R., Küng, J., Thoai, N., Takizawa, M., Neuhold, E. (eds) Future Data and Security Engineering. FDSE 2017. Lecture Notes in Computer Science(), vol 10646. Springer, Cham. https://doi.org/10.1007/978-3-319-70004-5_30
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