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DORIS: Personalized course recommendation system based on deep learning.

Authors :
Ma, Yinping
Ouyang, Rongbin
Long, Xinzheng
Gao, Zhitong
Lai, Tianping
Fan, Chun
Source :
PLoS ONE. 6/2/2023, Vol. 17 Issue 6, p1-14. 14p.
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
17
Issue :
6
Database :
Academic Search Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
164086947
Full Text :
https://doi.org/10.1371/journal.pone.0284687