Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Research on Personalized Course Recommendation Algorithm Based on Att-CIN-DNN under Online Education Cloud Platform

  • Xiaoqiang Liu (College of Applied Engineering, Henan University of Science and Technology) ;
  • Feng Hou (College of Applied Engineering, Henan University of Science and Technology)
  • Received : 2023.02.23
  • Accepted : 2023.09.02
  • Published : 2024.06.30
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Abstract

A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.

Keywords

References

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