Link Prediction On Fb15K

Hits@10

MRR

Résultats

Résultats de performance de divers modèles sur ce benchmark

Tableau comparatif

Nom du modèle	Hits@10	MRR
augmenting-and-tuning-knowledge-graph	0.914	0.841
adaptive-convolution-for-multi-relational	0.887	0.782
tucker-tensor-factorization-for-knowledge	0.892	0.795
logicenn-a-neural-based-knowledge-graphs	0.874	0.766
Modèle 5	0.842	0.696
seek-segmented-embedding-of-knowledge-graphs	0.886	0.825
quaternion-knowledge-graph-embedding	0.900	0.833
knowledge-graph-completion-via-complex-tensor	0.840	0.692
representation-learning-with-ordered-relation	0.899	-
rotate-knowledge-graph-embedding-by	0.884	0.799
convolutional-2d-knowledge-graph-embeddings	0.831	0.657
hypernetwork-knowledge-graph-embeddings	0.885	0.790
graphvite-a-high-performance-cpu-gpu-hybrid	0.876	0.779
simple-embedding-for-link-prediction-in	0.838	0.727
augmenting-compositional-models-for-knowledge	.901	.796
autokge-searching-scoring-functions-for	0.914	0.861
multi-partition-embedding-interaction-with	0.893	0.806
nscaching-simple-and-efficient-negative	-	0.7721
rotate-knowledge-graph-embedding-by	0.884	0.797
convolutional-2d-knowledge-graph-embeddings	0.660	0.660
knowledge-graph-embedding-via-dynamic-mapping	0.773	-
using-pairwise-occurrence-information-to	0.883	0.761
translating-embeddings-for-modeling-multi	0.471	-