Design of Intelligent Online Education Resource Optimization and Scheduling Strategies Based on Deep Reinforcement Learning
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24. Sept. 2025
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Online veröffentlicht: 24. Sept. 2025
Eingereicht: 25. Dez. 2024
Akzeptiert: 24. Apr. 2025
DOI: https://doi.org/10.2478/amns-2025-1106
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© 2025 Yen Chun Lee et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.

Figure 2.

Figure 3.

Statistics for Datasets
- | School Digital Library Data | Goodbooks-10k data |
---|---|---|
Borrowing records | 518806 | 898287 |
Users | 22683 | 41,482 |
Books | 124357 | 10,000 |
Training data | 496,044 | 856,772 |
Test data | 22,581 | 41,425 |
Comparative experimental results of Goodbooks-10k data
- | HR@5 | HR@10 | NDCG@5 | NDCG@10 |
---|---|---|---|---|
CF | 0.4073 | 0.5755 | 0.1013 | 0.1212 |
FISM | 0.4019 | 0.5441 | 0.2783 | 0.325 |
NAIS | 0.3553 | 0.4989 | 0.2432 | 0.289 |
Light-GCN | 0.4301 | 0.5935 | 0.2814 | 0.3467 |
HRL | 0.2152 | 0.3223 | 0.1638 | 0.1923 |
Model of this article | 0.4807 | 0.7023 | 0.3689 | 0.4389 |
Experimental results with different parameter settings
Category | HR@5 | HR@10 | NDCG@5 | NDCG@10 |
---|---|---|---|---|
10,000 | 0.3457 | 0.4063 | 0.2347 | 0.2579 |
5,000 | 0.652 | 0.7019 | 0.4959 | 0.5174 |
2,000 | 0.8294 | 0.922 | 0.5904 | 0.6204 |
1,000 | 0.8058 | 0.8973 | 0.5675 | 0.592 |
Comparative experimental results of school digital library data
- | HR@5 | HR@10 | NDCG@5 | NDCG@10 |
---|---|---|---|---|
CF | 0.4515 | 0.4873 | 0.2865 | 0.2728 |
FISM | 0.2355 | 0.3243 | 0.1781 | 0.2044 |
NAIS | 0.2143 | 0.2857 | 0.1598 | 0.1835 |
Light-GCN | 0.4695 | 0.5895 | 0.3233 | 0.3759 |
HRL | 0.6505 | 0.7824 | 0.4713 | 0.5159 |
Model of this article | 0.83 | 0.9222 | 0.5901 | 0.6219 |