A Self-Adaptive Recommendation Method for Online Ideological and Political Teaching Resources Based on Deep Reinforcement Learning

Ying Jin

DOI: 10.1155/2022/1702657
Published: 2022-08-29
Container: Mobile Information Systems
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1155/2022/1702657,
  title = {A Self-Adaptive Recommendation Method for Online Ideological and Political Teaching Resources Based on Deep Reinforcement Learning},
  author = {Ying Jin},
  year = {2022},
  journal = {Mobile Information Systems},
  doi = {10.1155/2022/1702657},
  url = {https://doi.org/10.1155/2022/1702657}
}

RIS

TY  - JOUR
TI  - A Self-Adaptive Recommendation Method for Online Ideological and Political Teaching Resources Based on Deep Reinforcement Learning
AU  - Ying Jin
PY  - 2022
JO  - Mobile Information Systems
DO  - 10.1155/2022/1702657
UR  - https://doi.org/10.1155/2022/1702657
ER  -

APA

Jin, Y. (2022). A Self-Adaptive Recommendation Method for Online Ideological and Political Teaching Resources Based on Deep Reinforcement Learning. Mobile Information Systems. https://doi.org/10.1155/2022/1702657

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crossref · retrieved 2026-09-25T04:32:03.005Z