PLoS ONE (Jan 2023)

DORIS: Personalized course recommendation system based on deep learning.

  • Yinping Ma,
  • Rongbin Ouyang,
  • Xinzheng Long,
  • Zhitong Gao,
  • Tianping Lai,
  • Chun Fan

DOI
https://doi.org/10.1371/journal.pone.0284687
Journal volume & issue
Vol. 18, no. 6
p. e0284687

Abstract

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Course recommendation aims at finding proper and attractive courses from massive candidates for students based on their needs, and it plays a significant role in the curricula-variable system. However, nearly all students nowadays need help selecting appropriate courses from abundant ones. The emergence and application of personalized course recommendations can release students from that cognitive overload problem. However, it still needs to mature and improve its scalability, sparsity, and cold start problems resulting in poor quality recommendations. Therefore, this paper proposes a novel personalized course recommendation system based on deep factorization machine (DeepFM), namely Deep PersOnalized couRse RecommendatIon System (DORIS), which selects the most appropriate courses for students according to their basic information, interests and the details of all courses. The experimental results illustrate that our proposed method outperforms other approaches.