Abstract
With the continuous development of networks, web-based e-learning is changing the way people acquire knowledge. An increasing number of learners are eager to acquire more knowledge through personalized and intelligent means. Based on content recommendation and collaborative filtering recommendation algorithm, this paper proposes a hybrid recommendation algorithm which can improve the efficiency of traditional recommendation algorithm. The presented research introduces the whole process of user interest model and teaching resources model, which also designs and implements the personalized network teaching resources system prototype. Finally, in comparison with the traditional recommendation algorithm, the improved hybrid recommendation algorithm has more advantages in personalized intelligent educational resources recommendation system.
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Acknowledgements
The research is supported by the Science and technology project of Lianyungang City, No.(JC1608). The research is supported by the top-notch Academic Programs Project of Jiangsu Higher Education Institution (PPZY2015a038), Qing Lan Project of Jiang Su Province, 521 personnel project of Lianyungang, Science Foundation of Huaihai Institute of Technology (Z2017012, Z2015012), Teaching reform research project of Huaihai Institute of Technology(XJG2017-2-5), Cooperation and Education Project of Ministry Education(201701028110, 201701028011, 201702134005).
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Li, H., Li, H., Zhang, S. et al. Intelligent learning system based on personalized recommendation technology. Neural Comput & Applic 31, 4455–4462 (2019). https://doi.org/10.1007/s00521-018-3510-5
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DOI: https://doi.org/10.1007/s00521-018-3510-5