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

Showing 676700 of 1949 papers

TitleStatusHype
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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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoKGEHits@100.56Unverified
2CP-N3-RPHits@100.55Unverified
3DistMult (after variational EM)Hits@100.55Unverified
4KG-R3Hits@100.54Unverified
5LASSHits@100.53Unverified
6MDE_advHits@100.53Unverified
7GFA-NNHits@100.52Unverified
8KGRefinerHits@100.49Unverified
9ComplEx NSCachingHits@100.48Unverified
10LogicENNHits@100.47Unverified
#ModelMetricClaimedVerifiedStatus
1MoCoKGCHits@100.88Unverified
2KERMITHits@100.83Unverified
3MoCoSAHits@100.82Unverified
4SimKGCIB(+PB+SN)Hits@100.82Unverified
5C-LMKE(bert-base)Hits@100.79Unverified
6LASSHits@100.79Unverified
7LP-BERTHits@100.75Unverified
8KGLMHits@100.74Unverified
9StAR(Self-Adp)Hits@100.71Unverified
10PALTHits@100.69Unverified
#ModelMetricClaimedVerifiedStatus
1OpenKE (han2018openke)training time (s)11Unverified
2LibKGE (ruffinelli2020you)training time (s)10Unverified
3GraphVite (zhu2019graphvite)training time (s)6Unverified
4Inverse ModelHits@100.96Unverified
5QuatDEHits@100.96Unverified
6LineaREHits@100.96Unverified
7AutoKGEHits@100.96Unverified
8MEI (small)Hits@100.96Unverified
9ComplEx-N3 (reciprocal)Hits@100.96Unverified
10RotatEHits@100.96Unverified
#ModelMetricClaimedVerifiedStatus
1OPTransEHits@100.9Unverified
2AutoKGEMRR0.86Unverified
3ComplEx-N3 (reciprocal)MRR0.86Unverified
4LineaREMRR0.84Unverified
5DistMult (after variational EM)MRR0.84Unverified
6QuatEMRR0.83Unverified
7SEEKMRR0.83Unverified
8MEI-BTDMRR0.81Unverified
9MEI (small)MRR0.8Unverified
10pRotatEMRR0.8Unverified