Link Prediction On Yago3 10
Métriques
Hits@1
Hits@10
Hits@3
MRR
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Hits@1 | Hits@10 | Hits@3 | MRR |
|---|---|---|---|---|
| rot-pro-modeling-transitivity-by-projection | 0.443 | 0.699 | 0.596 | 0.542 |
| learning-hierarchy-aware-knowledge-graph | 0.462 | 0.694 | 0.596 | 0.545 |
| start-small-think-big-on-hyperparameter | - | - | - | 0.551 |
| boxe-a-box-embedding-model-for-knowledge-base | 0.494 | 0.699 | - | 0.567 |
| low-dimensional-hyperbolic-knowledge-graph-1 | 0.503 | 0.712 | 0.621 | 0.577 |
| duality-induced-regularizer-for-tensor | 0.506 | 0.709 | - | 0.579 |
| dense-an-enhanced-non-abelian-group | 0.465 | 0.678 | 0.585 | 0.541 |
| duality-induced-regularizer-for-tensor | 0.511 | 0.713 | - | 0.584 |
| 190600687 | 0.381 | 0.643 | 0.523 | 0.472 |
| safran-an-interpretable-rule-based-link | 0.492 | 0.693 | - | 0.564 |
| neural-bellman-ford-networks-a-general-graph | 0.480 | 0.708 | 0.612 | 0.563 |
| multi-partition-embedding-interaction-with | 0.505 | 0.709 | 0.622 | 0.578 |
| Modèle 13 | 0.470 | 0.707 | 0.611 | 0.556 |
| meim-multi-partition-embedding-interaction | 0.514 | 0.716 | 0.625 | 0.585 |
| canonical-tensor-decomposition-for-knowledge | - | - | - | 0.58 |
| interacte-improving-convolution-based | 0.462 | 0.687 | - | 0.541 |
| convolutional-2d-knowledge-graph-embeddings | - | 0.62 | - | 0.44 |
| canonical-tensor-decomposition-for-knowledge | - | 0.71 | - | - |