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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1276–1300 of 1949 papers

TitleStatusHype
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