Research map / Reinforcement learning / Visual and representation RL
Hierarchical Reinforcement Learning for Course Recommendation in MOOCs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add HRL profile reviser to NAIS | NAIS · XuetangX | HR@10: 69.05 -> 79.68 | Helped |
| add HRL profile reviser to NASR | NASR · XuetangX | HR@10: 69.48 -> 74.50 | Helped |
| add HRL profile reviser to NAIS | NAIS · XuetangX | NDCG@10: 47.82 -> 50.69 | Helped |
| add high-level task (HRL vs one-level RL) (ablation) | RL+NAIS · XuetangX | HR/NDCG: ~ 4.29 | Helped |
| learned HRL revision instead of greedy threshold revision (ablation) | NAIS · XuetangX | HR@10: 77.44% -> 79.68 | Helped |
Closest papers by meaning
- Multi-type MOOCs Recommendation: Leveraging Deep Multi-Relational Representation and Hierarchical Reasoning (AAAI 2025 · similarity 0.89)
- Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing (NeurIPS 2025 · similarity 0.84)
- On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation (ICML 2024 · similarity 0.83)
- MRMLREC: A Two-Stage Approach for Addressing Data Sparsity in MOOC Video Recommendation (Student Abstract) (AAAI 2024 · similarity 0.83)
- Get a Head Start: On-Demand Pedagogical Policy Selection in Intelligent Tutoring (AAAI 2024 · similarity 0.82)
- GenAL: Generative Agent for Adaptive Learning (AAAI 2025 · similarity 0.81)
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