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 1076–1100 of 1949 papers

TitleStatusHype
Anchor Prediction: A Topic Modeling Approach—0
Learning Graph Embedding with Adversarial Training Methods—0
DINE: A Framework for Deep Incomplete Network Embedding—0
Learning Graph Representations—0
SPAN: Subgraph Prediction Attention Network for Dynamic Graphs—0
Learning Graph Structure from Convolutional Mixtures—0
Diffusion Maps for Textual Network Embedding—0
Diffusing Graph Attention—0
Learning Meta Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction—0
Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks—0
Learning Numerical Attributes in Knowledge Bases—0
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks—0
Degree-Based Random Walk Approach for Graph Embedding—0
Defeats GAN: A Simpler Model Outperforms in Knowledge Representation Learning—0
Learning Relational Features with Backward Random Walks—0
Learning Representation over Dynamic Graph using Aggregation-Diffusion Mechanism—0
DeepTrax: Embedding Graphs of Financial Transactions—0
Learning Representations of Entities and Relations—0
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications—0
Learning Robust Representations with Graph Denoising Policy Network—0
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures—0
Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks—0
Learning Social Image Embedding with Deep Multimodal Attention Networks—0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
Learning to Borrow– Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion—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
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