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 1676–1700 of 1949 papers

TitleStatusHype
Is a Single Vector Enough? Exploring Node Polysemy for Network EmbeddingCode0
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based ApproachCode0
Iteratively Learning Representations for Unseen Entities with Inter-Rule CorrelationsCode0
Jack the Reader -- A Machine Reading FrameworkCode0
JNET: Learning User Representations via Joint Network Embedding and Topic EmbeddingCode0
Joint Language Semantic and Structure Embedding for Knowledge Graph CompletionCode0
KBGAN: Adversarial Learning for Knowledge Graph EmbeddingsCode0
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationCode0
Kernel Node EmbeddingsCode0
KG-BERT: BERT for Knowledge Graph CompletionCode0
Knowledge Base Completion: Baseline strikes back (Again)Code0
Regex Queries over Incomplete Knowledge BasesCode0
Knowledge Generation -- Variational Bayes on Knowledge GraphsCode0
Knowledge Graph Completion via Complex Tensor FactorizationCode0
Knowledge Graph Completion with Mixed Geometry Tensor FactorizationCode0
Knowledge Graph Embedding by Translating on HyperplanesCode0
Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy TasksCode0
Knowledge Graph Embedding via Dynamic Mapping MatrixCode0
Knowledge Graph Embedding with 3D Compound Geometric TransformationsCode0
Knowledge Graph Embedding with Iterative Guidance from Soft RulesCode0
Knowledge Hypergraph Embedding Meets Relational AlgebraCode0
LASE: Learned Adjacency Spectral EmbeddingsCode0
Leap: Inductive Link Prediction via Learnable TopologyAugmentationCode0
Learnable Spatial-Temporal Positional Encoding for Link PredictionCode0
Learning Attention-based Embeddings for Relation Prediction in Knowledge GraphsCode0
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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
8ComplEx-N3 (reciprocal)Hits@100.96—Unverified
9MEI (small)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