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 1701–1750 of 1949 papers

TitleStatusHype
TNE: A Latent Model for Representation Learning on Networks—0
Systematic Biases in Link Prediction: comparing heuristic and graph embedding based methods—0
Higher-order Spectral Clustering for Heterogeneous Graphs—0
Constructing Graph Node Embeddings via Discrimination of Similarity Distributions—0
Dual Convolutional Neural Network for Graph of Graphs Link Prediction—0
Classification Using Link PredictionCode0
Encoding Robust Representation for Graph GenerationCode0
Graph Generation via Scattering—0
Probabilistic Knowledge Graph Embeddings—0
Characterizing Malicious Edges targeting on Graph Neural Networks—0
Incorporating GAN for Negative Sampling in Knowledge Representation Learning—0
Improved Deep Embeddings for Inferencing with Multi-Layered Networks—0
Sampled in Pairs and Driven by Text: A New Graph Embedding Framework—0
Learning Sequence Encoders for Temporal Knowledge Graph CompletionCode0
dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation LearningCode0
Feature Learning for Meta-Paths in Knowledge Graphs—0
BiasedWalk: Biased Sampling for Representation Learning on GraphsCode0
Embedding Multimodal Relational Data for Knowledge Base CompletionCode0
AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation—0
Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions—0
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment—0
Predicting Semantic Relations using Global Graph PropertiesCode0
Hypernetwork Knowledge Graph EmbeddingsCode0
Towards Anticipation of Architectural Smells using Link Prediction Techniques—0
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search PersonalizationCode1
Can Network Analysis Techniques help to Predict Design Dependencies? An Initial Study—0
Global and local evaluation of link prediction tasks with neural embeddings—0
DeepLink: A Novel Link Prediction Framework based on Deep Learning—0
AceKG: A Large-scale Knowledge Graph for Academic Data Mining—0
LinkNBed: Multi-Graph Representation Learning with Entity Linkage—0
Attention Models in Graphs: A SurveyCode0
Learning Deep Network Representations with Adversarially Regularized AutoencodersCode0
A Sequence Learning Method for Domain-Specific Entity Linking—0
Knowledge Graph Embedding with Numeric Attributes of Entities—0
Towards Understanding the Geometry of Knowledge Graph EmbeddingsCode0
Type-Sensitive Knowledge Base Inference Without Explicit Type SupervisionCode0
Jack the Reader -- A Machine Reading FrameworkCode0
Hierarchical Graph Representation Learning with Differentiable PoolingCode1
Jack the Reader - A Machine Reading FrameworkCode1
Canonical Tensor Decomposition for Knowledge Base CompletionCode1
Spectral Network Embedding: A Fast and Scalable Method via Sparsity—0
Scientific Discovery as Link Prediction in Influence and Citation Graphs—0
Accurate Text-Enhanced Knowledge Graph Representation Learning—0
Diffusion Maps for Textual Network Embedding—0
Conditional Network Embeddings—0
GANE: A Generative Adversarial Network Embedding—0
Learning Heterogeneous Knowledge Base Embeddings for Explainable RecommendationCode0
Billion-scale Network Embedding with Iterative Random ProjectionCode0
t-PINE: Tensor-based Predictable and Interpretable Node Embeddings—0
RECS: Robust Graph Embedding Using Connection Subgraphs—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