DORIS: Personalized course recommendation system based on deep learning.

Journal: PloS one
PMID:

Abstract

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.

Authors

  • Yinping Ma
    Computer Center, Peking University, Beijing, China.
  • Rongbin Ouyang
    Computer Center, Peking University, Beijing, China.
  • Xinzheng Long
    Computer Center, Peking University, Beijing, China.
  • Zhitong Gao
    Computer Center, Peking University, Beijing, China.
  • Tianping Lai
    Computer Center, Peking University, Beijing, China.
  • Chun Fan
    Computer Center, Peking University, Beijing, China.