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 651–700 of 1949 papers

TitleStatusHype
IRT2: Inductive Linking and Ranking in Knowledge Graphs of Varying ScaleCode0
Investigating Robustness and Interpretability of Link Prediction via Adversarial ModificationsCode0
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social ContextsCode0
Joint Language Semantic and Structure Embedding for Knowledge Graph CompletionCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Is a Single Vector Enough? Exploring Node Polysemy for Network EmbeddingCode0
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and EmbeddingCode0
Kernel Node EmbeddingsCode0
Faster Graph Embeddings via CoarseningCode0
On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction MethodsCode0
Knowledge Base Completion: Baseline strikes back (Again)Code0
Regex Queries over Incomplete Knowledge BasesCode0
Interpretable Signed Link Prediction with Signed Infomax Hyperbolic GraphCode0
Invariant Link Selector for Spatial-Temporal Out-of-Distribution ProblemCode0
Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation ExtractionCode0
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationCode0
Locally Private Bayesian Inference for Count ModelsCode0
Free Energy Node Embedding via Generalized Skip-gram with Negative SamplingCode0
Frequent Pattern Mining in Continuous-time Temporal NetworksCode0
A Hidden Challenge of Link Prediction: Which Pairs to Check?Code0
Inferring Networks of Substitutable and Complementary ProductsCode0
FakeEdge: Alleviate Dataset Shift in Link PredictionCode0
Reliable Time Prediction in the Markov Stochastic Block ModelCode0
Influence-guided Data Augmentation for Neural Tensor CompletionCode0
Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community InfluencesCode0
Inductive Logical Query Answering in Knowledge GraphsCode0
Context-aware Event Forecasting via Graph DisentanglementCode0
Future Link Prediction Without Memory or AggregationCode0
Inductive Link Prediction in Knowledge Graphs using Path-based Neural NetworksCode0
A Hierarchical Block Distance Model for Ultra Low-Dimensional Graph RepresentationsCode0
Inductive Link Prediction on N-ary Relational Facts via Semantic Hypergraph ReasoningCode0
Learning Based Proximity Matrix Factorization for Node EmbeddingCode0
Asymptotics of _2 Regularized Network EmbeddingsCode0
Learning Edge Representations via Low-Rank Asymmetric ProjectionsCode0
Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex SpacesCode0
Dynamic Embedding on Textual Networks via a Gaussian ProcessCode0
Companion Animal Disease Diagnostics based on Literal-aware Medical Knowledge Graph Representation LearningCode0
Expressive Higher-Order Link Prediction through Hypergraph Symmetry BreakingCode0
Independent Distribution Regularization for Private Graph EmbeddingCode0
Inductive Knowledge Graph Completion with GNNs and Rules: An AnalysisCode0
Exploring Time Granularity on Temporal Graphs for Dynamic Link Prediction in Real-world NetworksCode0
Exploring the Role of Node Diversity in Directed Graph Representation LearningCode0
Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic GraphsCode0
Exploring the Performance of Continuous-Time Dynamic Link Prediction AlgorithmsCode0
A Survey of Link Prediction in N-ary Knowledge GraphsCode0
A Systematic Investigation of KB-Text Embedding Alignment at ScaleCode0
Structural Group Unfairness: Measurement and Mitigation by means of the Effective ResistanceCode0
Learning Sequence Encoders for Temporal Knowledge Graph CompletionCode0
Generative-Contrastive Heterogeneous Graph Neural NetworkCode0
FILDNE: A Framework for Incremental Learning of Dynamic Networks EmbeddingsCode0
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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