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 751–800 of 1949 papers

TitleStatusHype
Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks—0
NestE: Modeling Nested Relational Structures for Knowledge Graph ReasoningCode0
Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction PredictionCode0
Redefining Developer Assistance: Through Large Language Models in Software Ecosystem—0
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning—0
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction—0
Beyond Transduction: A Survey on Inductive, Few Shot, and Zero Shot Link Prediction in Knowledge Graphs—0
Dyport: Dynamic Importance-based Hypothesis Generation Benchmarking TechniqueCode0
On the Initialization of Graph Neural NetworksCode0
Normed Spaces for Graph EmbeddingCode0
A Review of Link Prediction Applications in Network Biology—0
Knowledge Graph Reasoning Based on Attention GCN—0
Location Sensitive Embedding for Knowledge Graph Reasoning—0
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers—0
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic GraphsCode0
Exploring Time Granularity on Temporal Graphs for Dynamic Link Prediction in Real-world NetworksCode0
Cross-View Graph Consistency Learning for Invariant Graph RepresentationsCode0
Self-Supervised Pretraining for Heterogeneous Hypergraph Neural Networks—0
Knowledge Graphs are not Created Equal: Exploring the Properties and Structure of Real KGs—0
Unifying Structure and Language Semantic for Efficient Contrastive Knowledge Graph Completion with Structured Entity Anchors—0
Edge2Node: Reducing Edge Prediction to Node Classification—0
Causal Question Answering with Reinforcement LearningCode0
Cooperative Network Learning for Large-Scale and Decentralized GraphsCode0
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach—0
Community Detection Guarantees Using Embeddings Learned by Node2Vec—0
DyExplainer: Explainable Dynamic Graph Neural Networks—0
Enhancing Dense Retrievers' Robustness with Group-level ReweightingCode0
Balancing Augmentation with Edge-Utility Filter for Signed GNNs—0
Graph Agent: Explicit Reasoning Agent for Graphs—0
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning—0
Universal Knowledge Graph EmbeddingsCode0
A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of ThingsCode0
Emulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules—0
Towards Enhancing Relational Rules for Knowledge Graph Link PredictionCode0
Exploring Graph Neural Networks for Indian Legal Judgment Prediction—0
A Benchmark for Semi-Inductive Link Prediction in Knowledge GraphsCode0
Privacy-Preserving Graph Embedding based on Local Differential PrivacyCode0
Accurate prediction of international trade flows: Leveraging knowledge graphs and their embeddings—0
Network Analysis of the iNaturalist Citizen Science Community—0
Dynamic Link Prediction for New Nodes in Temporal Graph Networks—0
Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph EmbeddingCode0
Efficient Link Prediction via GNN Layers Induced by Negative SamplingCode0
Expanding the Vocabulary of BERT for Knowledge Base ConstructionCode0
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems—0
Hybrid Recommendation System using Graph Neural Network and BERT Embeddings—0
ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding—0
A Topological Perspective on Demystifying GNN-Based Link Prediction PerformanceCode0
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional NetworksCode0
DINE: Dimensional Interpretability of Node EmbeddingsCode0
Deep Insights into Noisy Pseudo Labeling on Graph DataCode0
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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