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 1251–1300 of 1949 papers

TitleStatusHype
Out-of-Vocabulary Entities in Link PredictionCode0
Self-Supervised Graph Representation Learning via Topology TransformationsCode0
Graph Based Link Prediction between Human Phenotypes and Genes—0
Predicting Links on Wikipedia with Anchor Text Information—0
Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative PositionsCode0
A Robust and Generalized Framework for Adversarial Graph EmbeddingCode0
Auxiliary learning induced graph convolutional networks—0
A Preference Random Walk Algorithm for Link Prediction through Mutual Influence Nodes in Complex Networks—0
Free Energy Node Embedding via Generalized Skip-gram with Negative SamplingCode0
QuatDE: Dynamic Quaternion Embedding for Knowledge Graph CompletionCode0
Link Prediction on N-ary Relational Facts: A Graph-based ApproachCode0
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective—0
Neural-Symbolic Commonsense Reasoner with Relation Predictors—0
Frequent Pattern Mining in Continuous-time Temporal NetworksCode0
Graph Learning: A Survey—0
ResVGAE: Going Deeper with Residual Modules for Link Prediction—0
MUSE: Multi-faceted Attention for Signed Network Embedding—0
FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation LearningCode0
Unsupervised Deep Manifold Attributed Graph EmbeddingCode0
Network Embedding via Deep Prediction Model—0
Seastar: vertex-centric programming for graph neural networks—0
HYPER^2: Hyperbolic Poincare Embedding for Hyper-Relational Link Prediction—0
Locate Who You Are: Matching Geo-location to Text for User Identity Linkage—0
CEAR: Cross-Entity Aware Reranker for Knowledge Base Completion—0
Membership Inference Attacks on Knowledge Graphs—0
A Hyperbolic-to-Hyperbolic Graph Convolutional Network—0
Personalized Bundle Recommendation in Online Games—0
Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood—0
On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs—0
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph EmbeddingsCode0
Edge: Enriching Knowledge Graph Embeddings with External Text—0
mSHINE: A Multiple-meta-paths Simultaneous Learning Framework for Heterogeneous Information Network EmbeddingCode0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
Modeling Graph Node Correlations with Neighbor Mixture Models—0
Hyperbolic Geometry is Not Necessary: Lightweight Euclidean-Based Models for Low-Dimensional Knowledge Graph Embeddings—0
The unknown knowns: a graph-based approach for temporal COVID-19 literature miningCode0
Deepened Graph Auto-Encoders Help Stabilize and Enhance Link PredictionCode0
Social Link Inference via Multi-View Matching Network from Spatio-Temporal Trajectories—0
GCN-ALP: Addressing Matching Collisions in Anchor Link Prediction—0
ChronoR: Rotation Based Temporal Knowledge Graph Embedding—0
Collaborative Filtering Approach to Link Prediction—0
DynACPD Embedding Algorithm for Prediction Tasks in Dynamic Networks—0
A Neural Network for SemigroupsCode0
Metapaths guided Neighbors aggregated Network for?Heterogeneous Graph Reasoning—0
A Relational-learning Perspective to Multi-label Chest X-ray Classification—0
Scalable Hypergraph Embedding System—0
Universal Representation for Code—0
Benchmarking Graph Neural Networks on Link Prediction—0
Graphfool: Targeted Label Adversarial Attack on Graph Embedding—0
Pre-Training on Dynamic Graph Neural NetworksCode0
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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