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 476–500 of 1949 papers

TitleStatusHype
Domain Representation for Knowledge Graph Embedding—0
Domain Generalization Deep Graph Transformation—0
Dual Graph Embedding for Object-Tag LinkPrediction on the Knowledge Graph—0
FOBE and HOBE: First- and High-Order Bipartite Embeddings—0
ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding—0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
DURENDAL: Graph deep learning framework for temporal heterogeneous networks—0
DVE: Dynamic Variational Embeddings with Applications in Recommender Systems—0
Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure—0
DyExplainer: Explainable Dynamic Graph Neural Networks—0
Biomedical Network Link Prediction using Neural Network Graph Embedding—0
DOLORES: Deep Contextualized Knowledge Graph Embeddings—0
Beyond Transduction: A Survey on Inductive, Few Shot, and Zero Shot Link Prediction in Knowledge Graphs—0
Does Link Prediction Help Detect Feature Interactions in Software Product Lines (SPLs)?—0
Node-Time Conditional Prompt Learning In Dynamic Graphs—0
DynACPD Embedding Algorithm for Prediction Tasks in Dynamic Networks—0
Bipartite Link Prediction based on Topological Features via 2-hop Path—0
Dynamic Graph Embedding via LSTM History Tracking—0
A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers—0
FMGNN: Fused Manifold Graph Neural Network—0
Forward Backward Similarity Search in Knowledge Networks—0
Document Network Projection in Pretrained Word Embedding Space—0
Dynamic Link and Flow Prediction in Bank Transfer Networks—0
DocGraphLM: Documental Graph Language Model for Information Extraction—0
Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks—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
8ComplEx-N3 (reciprocal)Hits@100.96—Unverified
9MEI (small)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