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 1901–1949 of 1949 papers

TitleStatusHype
Self-Supervised Graph Representation Learning via Global Context Prediction—0
Trivial bundle embeddings for learning graph representations—0
Inductive Representation Learning in Large Attributed Graphs—0
A Relation-Interactive Approach for Message Passing in Hyper-relational Knowledge Graphs—0
Document Network Projection in Pretrained Word Embedding Space—0
DocGraphLM: Documental Graph Language Model for Information Extraction—0
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath—0
Inference over Unseen Entities, Relations and Literals on Knowledge Graphs—0
A Relational Tucker Decomposition for Multi-Relational Link Prediction—0
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction—0
Self-Supervised Pretraining for Heterogeneous Hypergraph Neural Networks—0
Influence Maximization (IM) in Complex Networks with Limited Visibility Using Statistical Methods—0
Influence of Backdoor Paths on Causal Link Prediction—0
In-n-Out: Calibrating Graph Neural Networks for Link Prediction—0
Input Snapshots Fusion for Scalable Discrete Dynamic Graph Nerual Networks—0
InstantEmbedding: Efficient Local Node Representations—0
Instruction-based Hypergraph Pretraining—0
Integrating Heterogeneous Domain Information into Relation Extraction: A Case Study on Drug-Drug Interaction Extraction—0
Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models—0
Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing—0
Semantically Smooth Knowledge Graph Embedding—0
Semantic Entity Enrichment by Leveraging Multilingual Descriptions for Link Prediction—0
Integrating Transductive And Inductive Embeddings Improves Link Prediction Accuracy—0
A Relational-learning Perspective to Multi-label Chest X-ray Classification—0
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs—0
Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks—0
Interaction Order Prediction for Temporal Graphs—0
Are Hyperbolic Representations in Graphs Created Equal?—0
InterHT: Knowledge Graph Embeddings by Interaction between Head and Tail Entities—0
Semi-supervised Graph Embedding Approach to Dynamic Link Prediction—0
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs—0
Semi-supervised Network Embedding with Differentiable Deep Quantisation—0
Introducing New Node Prediction in Graph Mining: Predicting All Links from Isolated Nodes with Graph Neural Networks—0
Introducing RezoJDM16k: a French KnowledgeGraph DataSet for Link Prediction—0
Semi-supervised Training for Knowledge Base Graph Self-attention Networks on Link Prediction—0
Investigating Extensions to Random Walk Based Graph Embedding—0
A Probit Tensor Factorization Model For Relational Learning—0
SENSE: Semantically Enhanced Node Sequence Embedding—0
Investigating the Effect of Relative Positional Embeddings on AMR-to-Text Generation with Structural Adapters—0
Sequence-to-Sequence Knowledge Graph Completion and Question Answering—0
A Preference Random Walk Algorithm for Link Prediction through Mutual Influence Nodes in Complex Networks—0
SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network—0
Is Complex Query Answering Really Complex?—0
IS-GGT: Iterative Scene Graph Generation With Generative Transformers—0
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning—0
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning—0
Applying Universal Schemas for Domain Specific Ontology Expansion—0
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning—0
Shedding Light on Problems with Hyperbolic Graph Learning—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