SOTAVerified

Link Prediction

Link Prediction is a task in graph and network analysis where the goal is to predict missing or future connections between nodes in a network. Given a partially observed network, the goal of link prediction is to infer which links are most likely to be added or missing based on the observed connections and the structure of the network.

( Image credit: Inductive Representation Learning on Large Graphs )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1751–1775 of 1949 papers

TitleStatusHype
AceKG: A Large-scale Knowledge Graph for Academic Data Mining—0
LinkNBed: Multi-Graph Representation Learning with Entity Linkage—0
Attention Models in Graphs: A SurveyCode0
Learning Deep Network Representations with Adversarially Regularized AutoencodersCode0
Knowledge Graph Embedding with Numeric Attributes of Entities—0
Towards Understanding the Geometry of Knowledge Graph EmbeddingsCode0
A Sequence Learning Method for Domain-Specific Entity Linking—0
Type-Sensitive Knowledge Base Inference Without Explicit Type SupervisionCode0
Jack the Reader -- A Machine Reading FrameworkCode0
Spectral Network Embedding: A Fast and Scalable Method via Sparsity—0
Scientific Discovery as Link Prediction in Influence and Citation Graphs—0
Accurate Text-Enhanced Knowledge Graph Representation Learning—0
Diffusion Maps for Textual Network Embedding—0
Conditional Network Embeddings—0
GANE: A Generative Adversarial Network Embedding—0
Learning Heterogeneous Knowledge Base Embeddings for Explainable RecommendationCode0
Billion-scale Network Embedding with Iterative Random ProjectionCode0
RECS: Robust Graph Embedding Using Connection Subgraphs—0
t-PINE: Tensor-based Predictable and Interpretable Node Embeddings—0
Fast and scalable learning of neuro-symbolic representations of biomedical knowledge—0
Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network EmbeddingCode0
Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of NodesCode0
Graphite: Iterative Generative Modeling of GraphsCode0
Locally Private Bayesian Inference for Count ModelsCode0
Expeditious Generation of Knowledge Graph EmbeddingsCode0
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All datasetsFB15k-237WN18RRWN18FB15kYAGO3-10ICEWS05-15ICEWS14CiteseerCoraPubmedWikidata5MGDELT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoKGEHits@100.56—Unverified
2CP-N3-RPHits@100.55—Unverified
3DistMult (after variational EM)Hits@100.55—Unverified
4KG-R3Hits@100.54—Unverified
5LASSHits@100.53—Unverified
6MDE_advHits@100.53—Unverified
7GFA-NNHits@100.52—Unverified
8KGRefinerHits@100.49—Unverified
9ComplEx NSCachingHits@100.48—Unverified
10LogicENNHits@100.47—Unverified
#ModelMetricClaimedVerifiedStatus
1MoCoKGCHits@100.88—Unverified
2KERMITHits@100.83—Unverified
3MoCoSAHits@100.82—Unverified
4SimKGCIB(+PB+SN)Hits@100.82—Unverified
5C-LMKE(bert-base)Hits@100.79—Unverified
6LASSHits@100.79—Unverified
7LP-BERTHits@100.75—Unverified
8KGLMHits@100.74—Unverified
9StAR(Self-Adp)Hits@100.71—Unverified
10PALTHits@100.69—Unverified
#ModelMetricClaimedVerifiedStatus
1OpenKE (han2018openke)training time (s)11—Unverified
2LibKGE (ruffinelli2020you)training time (s)10—Unverified
3GraphVite (zhu2019graphvite)training time (s)6—Unverified
4Inverse ModelHits@100.96—Unverified
5QuatDEHits@100.96—Unverified
6LineaREHits@100.96—Unverified
7AutoKGEHits@100.96—Unverified
8MEI (small)Hits@100.96—Unverified
9ComplEx-N3 (reciprocal)Hits@100.96—Unverified
10RotatEHits@100.96—Unverified
#ModelMetricClaimedVerifiedStatus
1OPTransEHits@100.9—Unverified
2AutoKGEMRR0.86—Unverified
3ComplEx-N3 (reciprocal)MRR0.86—Unverified
4LineaREMRR0.84—Unverified
5DistMult (after variational EM)MRR0.84—Unverified
6QuatEMRR0.83—Unverified
7SEEKMRR0.83—Unverified
8MEI-BTDMRR0.81—Unverified
9MEI (small)MRR0.8—Unverified
10pRotatEMRR0.8—Unverified