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
MOHONE: Modeling Higher Order Network Effects in KnowledgeGraphs via Network Infused Embeddings—0
motif2vec: Motif Aware Node Representation Learning for Heterogeneous Networks—0
MotifDisco: Motif Causal Discovery For Time Series Motifs—0
Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations—0
Motif Prediction with Graph Neural Networks—0
Conformalized Answer Set Prediction for Knowledge Graph Embedding—0
MPRM: A Markov Path-based Rule Miner for Efficient and Interpretable Knowledge Graph Reasoning—0
ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions—0
MQuinE: a cure for "Z-paradox" in knowledge graph embedding models—0
Unified Graph Networks (UGN): A Deep Neural Framework for Solving Graph Problems—0
Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction—0
Symmetry-driven network reconstruction through pseudobalanced coloring optimization—0
Conditional Network Embeddings—0
MTRGL:Effective Temporal Correlation Discerning through Multi-modal Temporal Relational Graph Learning—0
MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings—0
Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles—0
Synthetic Graph Generation to Benchmark Graph Learning—0
Multi-frame Detection via Graph Neural Networks: A Link Prediction Approach—0
Systematic Biases in Link Prediction: comparing heuristic and graph embedding based methods—0
Deeper-GXX: Deepening Arbitrary GNNs—0
When Graph Neural Networks Meet Dynamic Mode Decomposition—0
MULTI-LEVEL APPROACH TO ACCURATE AND SCALABLE HYPERGRAPH EMBEDDING—0
Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction—0
Conditional Local Feature Encoding for Graph Neural Networks—0
Conditional Link Prediction of Category-Implicit Keypoint Detection—0
Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks—0
Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search—0
Unifying Structure and Language Semantic for Efficient Contrastive Knowledge Graph Completion with Structured Entity Anchors—0
Compositional Network Embedding—0
Composing Relationships with Translations—0
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings—0
Complex and Holographic Embeddings of Knowledge Graphs: A Comparison—0
Multi-Relational Graph Neural Network for Out-of-Domain Link Prediction—0
Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021—0
Comparison of Metadata Representation Models for Knowledge Graph Embeddings—0
MultiSAGE: a multiplex embedding algorithm for inter-layer link prediction—0
Multi-Scale Node Embeddings for Graph Modeling and Generation—0
Community detection in networks using graph embeddings—0
Aligning Knowledge and Text Embeddings by Entity Descriptions—0
Community Detection Guarantees Using Embeddings Learned by Node2Vec—0
Community Aware Random Walk for Network Embedding—0
Combinatorial Scientific Discovery: Finding New Concept Combinations Beyond Link Prediction—0
Multi-view graph structure learning using subspace merging on Grassmann manifold—0
MUSE: Multi-faceted Attention for Signed Network Embedding—0
Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models—0
Temporal-Amount Snapshot MultiGraph for Ethereum Transaction Tracking—0
M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search—0
A Hyperbolic-to-Hyperbolic Graph Convolutional Network—0
A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers—0
A2N: Attending to Neighbors for Knowledge Graph Inference—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