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 501–550 of 1949 papers

TitleStatusHype
Benchmarks for Graph Embedding EvaluationCode0
Dynamic Network Embedding via Incremental Skip-gram with Negative SamplingCode0
Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changesCode0
Iteratively Learning Representations for Unseen Entities with Inter-Rule CorrelationsCode0
Dyport: Dynamic Importance-based Hypothesis Generation Benchmarking TechniqueCode0
DyRep: Learning Representations over Dynamic GraphsCode0
Discriminative Predicate Path Mining for Fact Checking in Knowledge GraphsCode0
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based ApproachCode0
Bridging the Gap between Community and Node Representations: Graph Embedding via Community DetectionCode0
Jack the Reader -- A Machine Reading FrameworkCode0
Joint Language Semantic and Structure Embedding for Knowledge Graph CompletionCode0
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
Invariant Link Selector for Spatial-Temporal Out-of-Distribution ProblemCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Is a Single Vector Enough? Exploring Node Polysemy for Network EmbeddingCode0
Discovering emergent connections in quantum physics research via dynamic word embeddingsCode0
A Deep Sequential Model for Discourse Parsing on Multi-Party DialoguesCode0
On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction MethodsCode0
Interpretable Signed Link Prediction with Signed Infomax Hyperbolic GraphCode0
KBGAN: Adversarial Learning for Knowledge Graph EmbeddingsCode0
Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex SpacesCode0
A Deep Probabilistic Framework for Continuous Time Dynamic Graph GenerationCode0
Integrating Social Determinants of Health into Knowledge Graphs: Evaluating Prediction Bias and Fairness in HealthcareCode0
Inferring Networks of Substitutable and Complementary ProductsCode0
A Neural Network for SemigroupsCode0
Influence-guided Data Augmentation for Neural Tensor CompletionCode0
Integrating Structural and Semantic Signals in Text-Attributed Graphs with BiGTexCode0
Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific NetworksCode0
DINE: Dimensional Interpretability of Node EmbeddingsCode0
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural NetworkCode0
Reliable Time Prediction in the Markov Stochastic Block ModelCode0
InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature InteractionsCode0
Inductive Link Prediction on N-ary Relational Facts via Semantic Hypergraph ReasoningCode0
Inductive Logical Query Answering in Knowledge GraphsCode0
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter TuningCode0
Inductive Link Prediction in Knowledge Graphs using Path-based Neural NetworksCode0
Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community InfluencesCode0
Differentiating Concepts and Instances for Knowledge Graph EmbeddingCode0
Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic DecompositionCode0
A Deep Latent Space Model for Graph Representation LearningCode0
Inductive Knowledge Graph Completion with GNNs and Rules: An AnalysisCode0
Inter-domain Multi-relational Link PredictionCode0
Development of a Knowledge Graph Embeddings Model for PainCode0
Detecting drug-drug interactions using artificial neural networks and classic graph similarity measuresCode0
Derivation of Back-propagation for Graph Convolutional Networks using Matrix Calculus and its Application to Explainable Artificial IntelligenceCode0
DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic HierarchyCode0
Improving rule mining via embedding-based link predictionCode0
Incorporating Literals into Knowledge Graph 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