Top-N Recommendation on Netflix Prize Dataset
0.409NCDG@100H+Vamp Gated
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| H+Vamp Gated2021.02 | 0.409 | 37.6 | 46.3 | |
| VASP2021.02 | 0.406 | 37.2 | 45.7 | |
| FLVAE2021.02 | 0.398 | 36.3 | 45 | |
| RecVAE + PIAEncoder architecture=densely connected layers, Personalized Item Alignment=True2025.11 | 0.396 | 36.5 | 45.4 | |
| Neural EASE2021.02 | 0.395 | 36.3 | 44.7 | |
| RecVAE2021.02 | 0.394 | 36.1 | 45.2 | |
| RecVAEEncoder architecture=densely connected layers2025.11 | 0.394 | 36.1 | 45.2 | |
| EASE2021.02 | 0.393 | 36.2 | 44.5 | |
| EASEcategory=Matrix factorization & Linear regression2025.11 | 0.393 | 36.2 | 44.5 | |
| RaCTEncoder architecture=MLP2025.11 | 0.392 | 35.7 | 45 | |
| Multi-VAE + PIAEncoder architecture=MLP, Personalized Item Alignment=True2025.11 | 0.392 | 36 | 44.8 | |
| PLReccategory=Matrix factorization & Linear regression2025.11 | 0.39 | 35.7 | 44.1 | |
| Mult-VAE2021.02 | 0.386 | 35.1 | 44.4 | |
| LambdaNetcategory=Matrix factorization & Linear regression2025.11 | 0.386 | 35.2 | 44.1 | |
| Multi-VAEEncoder architecture=MLP2025.11 | 0.386 | 35.1 | 44.4 | |
| Mult-DAE2021.02 | 0.38 | 34.4 | 43.8 | |
| CDAEEncoder architecture=MLP2025.11 | 0.376 | 34.3 | 42.8 | |
| MFcategory=Matrix factorization & Linear regression2025.11 | 0.369 | 33.5 | 42.2 | |
| GRALScategory=Matrix factorization & Linear regression2025.11 | 0.365 | 33.5 | 41.6 | |
| WMFcategory=Matrix factorization & Linear regression2025.11 | 0.349 | 32.1 | 40.2 | |
| WARPcategory=Matrix factorization & Linear regression2025.11 | 0.312 | 27.3 | 36 | |
| Popularitycategory=Matrix factorization & Linear regression2025.11 | 0.159 | 11.6 | 17.5 |