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A content-based recommendation algorithm for learning resources

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Abstract

Automatic multimedia learning resources recommendation has become an increasingly relevant problem: it allows students to discover new learning resources that match their tastes, and enables the e-learning system to target the learning resources to the right students. In this paper, we propose a content-based recommendation algorithm based on convolutional neural network (CNN). The CNN can be used to predict the latent factors from the text information of the multimedia resources. To train the CNN, its input and output should first be solved. For its input, the language model is used. For its output, we propose the latent factor model, which is regularized by L 1-norm. Furthermore, the split Bregman iteration method is introduced to solve the model. The major novelty of the proposed recommendation algorithm is that the text information is used directly to make the content-based recommendation without tagging. Experimental results on public databases in terms of quantitative assessment show significant improvements over conventional methods. In addition, the split Bregman iteration method which is introduced to solve the model can greatly improve the training efficiency.

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Authors and Affiliations

  1. National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, Hubei, 430079, China

    Jiangbo Shu, Xiaoxuan Shen, Hai Liu, Baolin Yi & Zhaoli Zhang

Authors
  1. Jiangbo Shu
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  2. Xiaoxuan Shen
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  3. Hai Liu
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  4. Baolin Yi
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  5. Zhaoli Zhang
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Corresponding author

Correspondence to Xiaoxuan Shen.

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Funding

The authors thank the editor and anonymous reviewers for their valuable suggestions. This research was partially funded by the specific funding for education science research by self-determined research funds of CCNU from the colleges’ basic research and operation of MOE (CCNU16JYKX031 and CCNU16JYKX027), the National Natural Science Foundation of China under Grant (No. 61505064), the Project of the Program for National Key Technology Research and Development Program (2013BAH72B01, 2013BAH18F02, and 2015BAH33F02), and the Project of the Program for National Key Technology Research and Development Program (2014BAH22F01 and 2015BAK07B03).

Additional information

Communicated by B. Prabhakaran.

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Cite this article

Shu, J., Shen, X., Liu, H. et al. A content-based recommendation algorithm for learning resources. Multimedia Systems 24, 163–173 (2018). https://doi.org/10.1007/s00530-017-0539-8

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