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Link Prediction On Fb15K 1

Métriques

Hits@1

Hits@10

Hits@3

Hits@5

MRR

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Hits@1	Hits@10	Hits@3	Hits@5	MRR	Paper Title	Repository
Rule-Guided Embedding	0.703	0.865	0.815	0.836	0.768	Knowledge Graph Embedding with Iterative Guidance from Soft Rules
ComplEx NSCaching	-	0.8682	-	-	0.7721	NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
MEI (small)	0.757	0.878	0.823	-	0.800	Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion
ComplEx-N3 (reciprocal)	-	0.91	-	-	0.86	Canonical Tensor Decomposition for Knowledge Base Completion
ParTransH	-	0.468	-	-	-	Efficient Parallel Translating Embedding For Knowledge Graphs
HolE	0.402	0.739	0.613	-	0.524	Holographic Embeddings of Knowledge Graphs
HHolE	0.727	0.901	0.848	-	0.796	Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations	-
MDE	-	0.857	-	-	0.652	MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs
LineaRE	0.805	0.906	0.867	-	0.843	LineaRE: Simple but Powerful Knowledge Graph Embedding for Link Prediction
PyTorch BigGraph (ComplEx)	-	0.872	-	-	0.79	PyTorch-BigGraph: A Large-scale Graph Embedding System

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