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 1551–1575 of 1949 papers

TitleStatusHype
E-LSTM-D: A Deep Learning Framework for Dynamic Network Link PredictionCode0
Embedding Biomedical Ontologies by Jointly Encoding Network Structure and Textual Node DescriptorsCode0
Embedding Knowledge Graphs Attentive to Positional and Centrality QualitiesCode0
Embedding Multimodal Relational Data for Knowledge Base CompletionCode0
Embedding Ontologies via Incorporating Extensional and Intensional KnowledgeCode0
EM-RBR: a reinforced framework for knowledge graph completion from reasoning perspectiveCode0
Encoding Robust Representation for Graph GenerationCode0
End to end learning and optimization on graphsCode0
End-to-End Learning on Multimodal Knowledge GraphsCode0
End-to-end Structure-Aware Convolutional Networks for Knowledge Base CompletionCode0
Enhance Ambiguous Community Structure via Multi-strategy Community Related Link Prediction Method with Evolutionary ProcessCode0
Enhancing Future Link Prediction in Quantum Computing Semantic Networks through LLM-Initiated Node FeaturesCode0
Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization PerspectiveCode0
Enhancing the Expressivity of Temporal Graph Networks through Source-Target IdentificationCode0
Epitomic Variational Graph AutoencoderCode0
ERLKG: Entity Representation Learning and Knowledge Graph based association analysis of COVID-19 through mining of unstructured biomedical corporaCode0
Estimating network edge probabilities by neighborhood smoothingCode0
Estimation of Simultaneously Sparse and Low Rank MatricesCode0
Evaluating Link Prediction Explanations for Graph Neural NetworksCode0
Evaluating Overfit and Underfit in Models of Network Community StructureCode0
Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized DataCode0
ExEm: Expert Embedding using dominating set theory with deep learning approachesCode0
Expanding the Vocabulary of BERT for Knowledge Base ConstructionCode0
eXpath: Explaining Knowledge Graph Link Prediction with Ontological Closed Path RulesCode0
Expeditious Generation of 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
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