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 151–200 of 1949 papers

TitleStatusHype
Capturing and Anticipating User Intents in Data Analytics via Knowledge Graphs—0
How to Bridge Spatial and Temporal Heterogeneity in Link Prediction? A Contrastive Method—0
RAGraph: A General Retrieval-Augmented Graph Learning FrameworkCode1
Just Propagate: Unifying Matrix Factorization, Network Embedding, and LightGCN for Link Prediction—0
Can Self Supervision Rejuvenate Similarity-Based Link Prediction?—0
Geometric Feature Enhanced Knowledge Graph Embedding and Spatial Reasoning—0
Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production—0
Multi-frame Detection via Graph Neural Networks: A Link Prediction Approach—0
What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs—0
Is Complex Query Answering Really Complex?—0
CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype AssociationsCode0
Inference over Unseen Entities, Relations and Literals on Knowledge Graphs—0
When Graph Neural Networks Meet Dynamic Mode Decomposition—0
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter TuningCode0
Improving Temporal Link Prediction via Temporal Walk Matrix ProjectionCode1
Enhancing Future Link Prediction in Quantum Computing Semantic Networks through LLM-Initiated Node FeaturesCode0
Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge GraphsCode0
Improving Node Representation by Boosting Target-Aware Contrastive Loss—0
Mixed-curvature decision trees and random forestsCode2
ClassContrast: Bridging the Spatial and Contextual Gaps for Node Representations—0
PROXI: Challenging the GNNs for Link PredictionCode0
Replacing Paths with Connection-Biased Attention for Knowledge Graph CompletionCode0
Stabilizing the Kumaraswamy Distribution—0
Reevaluation of Inductive Link PredictionCode0
Explainable Enrichment-Driven GrAph Reasoner (EDGAR) for Large Knowledge Graphs with Applications in Drug RepurposingCode0
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks—0
Supra-Laplacian Encoding for Transformer on Dynamic GraphsCode0
Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)—0
MotifDisco: Motif Causal Discovery For Time Series Motifs—0
Higher-Order Message Passing for Glycan Representation LearningCode0
Signed Graph Autoencoder for Explainable and Polarization-Aware Network Embeddings—0
Towards understanding evolution of science through language model seriesCode0
Dynamic Link and Flow Prediction in Bank Transfer Networks—0
Promoting Fairness in Link Prediction with Graph Enhancement—0
Sub-graph Based Diffusion Model for Link Prediction—0
HyperCausalLP: Causal Link Prediction using Hyper-Relational Knowledge Graph—0
Influence of Backdoor Paths on Causal Link Prediction—0
Towards a graph-based foundation model for network traffic analysis—0
Dot Product is All You Need: Bridging the Gap Between Item Recommendation and Link Prediction—0
A Survey on Signed Graph Embedding: Methods and Applications—0
Reproducibility Study Of Learning Fair Graph Representations Via Automated Data AugmentationsCode0
Graph Attention Inference of Network Topology in Multi-Agent Systems—0
Learning Granularity Representation for Temporal Knowledge Graph CompletionCode0
LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token EmbeddingsCode2
RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification—0
Contrastive Representation Learning for Dynamic Link Prediction in Temporal NetworksCode1
Enhanced Expressivity in Graph Neural Networks with Lanczos-Based Linear Constraints—0
RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge GraphsCode0
GS-KGC: A Generative Subgraph-based Framework for Knowledge Graph Completion with Large Language Models—0
Predictive Multiplicity of Knowledge Graph Embeddings in 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