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

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Showing 1301–1350 of 1949 papers

TitleStatusHype
Type-Constrained Representation Learning in Knowledge Graphs—0
Efficient Parallel Multi-Hop Reasoning: A Scalable Approach for Knowledge Graph Analysis—0
Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks—0
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective—0
Understanding Generalization in Node and Link Prediction—0
Understanding graph embedding methods and their applications—0
Understanding Higher-order Structures in Evolving Graphs: A Simplicial Complex based Kernel Estimation Approach—0
Association Rules Enhanced Knowledge Graph Attention Network—0
Understanding the Mechanisms Behind Structural Influences on Link Prediction: A Case Study on FB15k-237—0
Efficient Personalized Community Detection via Genetic Evolution—0
Unified Graph Networks (UGN): A Deep Neural Framework for Solving Graph Problems—0
Efficient Relational Context Perception for Knowledge Graph Completion—0
Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search—0
Unifying Structure and Language Semantic for Efficient Contrastive Knowledge Graph Completion with Structured Entity Anchors—0
Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models—0
Efficient Variational Graph Autoencoders for Unsupervised Cross-domain Prerequisite Chains—0
Universal Link Predictor By In-Context Learning on Graphs—0
Universal Representation for Code—0
A statistical interpretation of spectral embedding: the generalised random dot product graph—0
Unsupervised Adversarial Graph Alignment with Graph Embedding—0
Unsupervised Adversarially-Robust Representation Learning on Graphs—0
Unsupervised Attributed Dynamic Network Embedding with Stability Guarantees—0
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs—0
Unsupervised Domain-adaptive Hash for Networks—0
Untargeted Adversarial Attack on Knowledge Graph Embeddings—0
Unveiling Hidden Links Between Unseen Security Entities—0
Updating Embeddings for Dynamic Knowledge Graphs—0
Adaptive Pseudo-Siamese Policy Network for Temporal Knowledge Prediction—0
Using Adamic-Adar Index Algorithm to Predict Volunteer Collaboration: Less is More—0
Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets—0
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs—0
Utilizing Graph Neural Networks for Effective Link Prediction in Microservice Architectures—0
UWN: A Large Multilingual Lexical Knowledge Base—0
Variational Disentangled Graph Auto-Encoders for Link Prediction—0
Variational Knowledge Graph Reasoning—0
V-Coder: Adaptive AutoEncoder for Semantic Disclosure in Knowledge Graphs—0
Vertex-Centric Visual Programming for Graph Neural Networks—0
Embedding Cardinality Constraints in Neural Link Predictors—0
VisGraphVar: A Benchmark Generator for Assessing Variability in Graph Analysis Using Large Vision-Language Models—0
VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs—0
Drug-Drug Interaction Prediction with Wasserstein Adversarial Autoencoder-based Knowledge Graph Embeddings—0
Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path—0
Weakly supervised collective feature learning from curated media—0
Weisfeiler-Lehman Embedding for Molecular Graph Neural Networks—0
5* Knowledge Graph Embeddings with Projective Transformations—0
When Graph Neural Networks Meet Dynamic Mode Decomposition—0
Empirical effect of graph embeddings on fraud detection/ risk mitigation—0
A Survey of Link Prediction in Temporal Networks—0
Why Settle for Just One? Extending EL++ Ontology Embeddings with Many-to-Many Relationships—0
wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction—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