Collaborative Filtering On Gowalla
المقاييس
NDCG@20
Recall@20
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
اسم النموذج | NDCG@20 | Recall@20 | Paper Title | Repository |
|---|---|---|---|---|
| LightGCN | 0.1554 | 0.1830 | LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation | - |
| SimpleX | 0.1557 | 0.1872 | SimpleX: A Simple and Strong Baseline for Collaborative Filtering | - |
| Emb-GCN | - | 0.1862 | UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation | - |
| NGCF | - | 0.1570 | Neural Graph Collaborative Filtering | - |
| BSPM-LM | 0.1570 | 0.1901 | Blurring-Sharpening Process Models for Collaborative Filtering | - |
| NESCL | 0.1617 | 0.1917 | Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering | - |
| LT-OCF | 0.1574 | 0.1875 | LT-OCF: Learnable-Time ODE-based Collaborative Filtering | - |
| UltraGCN | 0.1580 | 0.1862 | UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation | - |
| GF-CF | 0.1518 | 0.1849 | How Powerful is Graph Convolution for Recommendation? | - |
| BSPM-EM | 0.1597 | 0.1920 | Blurring-Sharpening Process Models for Collaborative Filtering | - |
0 of 10 row(s) selected.