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Design of Intelligent Online Education Resource Optimization and Scheduling Strategies Based on Deep Reinforcement Learning

Yen Chun Lee

Yen Chun Lee

  • Guangxi Key Laboratory of Big Data in Finance and Economics, Guangxi University of Finance and EconomicsNanning, China
  • School of Big Data and Artificial Intelligence, Guangxi University of Finance and EconomicsNanning, China
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Lee, Yen Chun
, 
Chao-We Hsu

Chao-We Hsu

Department of Information Management, Chaoyang University of TechnologyTaichung, China
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Hsu, Chao-We
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Chu-Hui Lee

Chu-Hui Lee

Department of Information Management, Chaoyang University of TechnologyTaichung, China
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Lee, Chu-Hui
  
24 wrz 2025
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Data publikacji: 24 wrz 2025
Otrzymano: 25 gru 2024
Przyjęty: 24 kwi 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.

Experimental results of different GCN layers on MOOPer dataset
Experimental results of different GCN layers on MOOPer dataset

Figure 2.

Experimental results of different GCN layers on MOOCCube dataset
Experimental results of different GCN layers on MOOCCube dataset

Figure 3.

Data sequence distribution
Data sequence distribution

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
Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne
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