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 1226–1250 of 1949 papers

TitleStatusHype
mGNN: Generalizing the Graph Neural Networks to the Multilayer Case—0
Weisfeiler-Lehman Embedding for Molecular Graph Neural Networks—0
Subgraph2vec: A random walk-based algorithm for embedding knowledge graphs—0
Context-Dependent Knowledge Graph Embedding—0
ALX: Large Scale Matrix Factorization on TPUs—0
MLMLM: Link Prediction with Mean Likelihood Masked Language Model—0
Context-Dependent Anomaly Detection with Knowledge Graph Embedding Models—0
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model—0
Mobile Link Prediction: Automated Creation and Crowd-sourced Validation of Knowledge Graphs—0
MoCoKGC: Momentum Contrast Entity Encoding for Knowledge Graph Completion—0
MoCoSA: Momentum Contrast for Knowledge Graph Completion with Structure-Augmented Pre-trained Language Models—0
Modeling Dynamic Environments with Scene Graph Memory—0
Constructing Graph Node Embeddings via Discrimination of Similarity Distributions—0
Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning—0
Modeling Graph Node Correlations with Neighbor Mixture Models—0
Constraint-based Multi-hop Question Answering with Knowledge Graph—0
Modeling Overlapping Communities with Node Popularities—0
Consistencies and inconsistencies between model selection and link prediction in networks—0
Sub-graph Based Diffusion Model for Link Prediction—0
Conformal retrofitting via Riemannian manifolds: distilling task-specific graphs into pretrained embeddings—0
Modeling the Evolution of Networks as Shrinking Structural Diversity—0
ALPINE: Active Link Prediction using Network Embedding—0
MODEL: Motif-based Deep Feature Learning for Link Prediction—0
Understanding the Mechanisms Behind Structural Influences on Link Prediction: A Case Study on FB15k-237—0
Conformalized Link Prediction on Graph Neural Networks—0
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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