MovieLens
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Recommendation | MovieLens | Accuracy97.9 | 84 | |
| Recommendation | MovieLens 100K (test) | RMSE0.883 | 55 | |
| CTR Prediction | MovieLens | AUC97.15 | 55 | |
| Vehicle Edge Caching | MovieLens 1M (test) | Cache Hit Rate53.05 | 48 | |
| Sequential Recommendation | MovieLens | ValidRatio1 | 41 | |
| Recommendation | MovieLens-1M (test) | Recall@36.06 | 34 | |
| Personalized Prediction | MovieLens (test) | Accuracy0.646 | 32 | |
| Matrix Completion | MovieLens-1M (test) | RMSE0.822 | 30 | |
| Recommendation | MovieLens small-scale | LCS Score66.8315 | 30 | |
| Rating Prediction | MovieLens 90/10 1M (train test) | RMSE0.829 | 27 | |
| Collaborative Filtering | MovieLens 1M (test) | RMSE0.829 | 25 | |
| Recommendation | MovieLens 20M (test) | Accuracy67.4 | 24 | |
| top-n recommendation | MovieLens 20M | NDCG@1000.448 | 22 | |
| Sequential Recommendation | MovieLens-1M (test) | Hit@1082.45 | 22 | |
| CTR prediction | MovieLens (test) | Logloss0.1857 | 21 | |
| Matrix Completion | MovieLens-100K (test) | RMSE0.897 | 21 | |
| Multi-task Regression | MovieLens (test) | Loss3,679 | 21 | |
| Recommendation | MovieLens latest (test) | Recall@1010.7084 | 20 | |
| CTR prediction | MovieLens 1M (test) | AUC94.49 | 19 | |
| Recommendation | MovieLens | NDCG@50.5765 | 18 | |
| Video Recommendation | MovieLens 10M (item cold-start) | MAP@50.0178 | 18 | |
| Video Recommendation | MovieLens item warm-start 10M | MAP@50.1536 | 18 | |
| Video Recommendation | MovieLens-10M item warm-start scenario | Shannon Entropy @58.0829 | 18 | |
| Recommender Systems | MovieLens item 10M (cold-start) | Div. SE @59.1818 | 18 | |
| Top-K Recommendation | MovieLens 20M (test) | Recall@5055.3 | 17 |
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