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홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

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Link Prediction On Fb15K 1

평가 지표

Hits@1

Hits@10

Hits@3

Hits@5

MRR

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	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	-

0 of 10 row(s) selected.

Link Prediction On Fb15K 1 | SOTA | HyperAI초신경