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 1851–1900 of 1949 papers

TitleStatusHype
Natural-Parameter Networks: A Class of Probabilistic Neural NetworksCode0
Limitations and Alternatives for the Evaluation of Large-scale Link Prediction—0
Encoding Temporal Information for Time-Aware Link Prediction—0
Jointly Embedding Knowledge Graphs and Logical Rules—0
Discriminative Gaifman Models—0
Semi-supervised Graph Embedding Approach to Dynamic Link Prediction—0
Improved Knowledge Base Completion by Path-Augmented TransR Model—0
Knowledge Representation via Joint Learning of Sequential Text and Knowledge Graphs—0
Learning Word Embeddings from Intrinsic and Extrinsic Views—0
Discriminative Deep Random Walk for Network Classification—0
A Discriminative Topic Model using Document Network Structure—0
Evaluating Link Prediction Accuracy on Dynamic Networks with Added and Removed Edges—0
Higher-Order Factorization MachinesCode0
node2vec: Scalable Feature Learning for NetworksCode1
Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks—0
subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large GraphsCode1
STransE: a novel embedding model of entities and relationships in knowledge basesCode0
Predict Anchor Links across Social Networks via an Embedding Approach—0
Link Prediction via Matrix Completion—0
Complex Embeddings for Simple Link PredictionCode2
Structural Deep Network EmbeddingCode0
Applying Universal Schemas for Domain Specific Ontology Expansion—0
A Translation-Based Knowledge Graph Embedding Preserving Logical Property of Relations—0
A Critical Examination of RESCAL for Completion of Knowledge Bases with Transitive Relations—0
Adaptive Candidate Generation for Scalable Edge-discovery Tasks on Data Graphs—0
Leveraging Network Dynamics for Improved Link Prediction—0
Max-Margin Nonparametric Latent Feature Models for Link Prediction—0
Machine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space—0
Log-Normal Matrix Completion for Large Scale Link Prediction—0
Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs—0
From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction—0
Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs—0
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation—0
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels—0
Halting in Random Walk Kernels—0
Handling Class Imbalance in Link Prediction using Learning to Rank Techniques—0
Discriminative Predicate Path Mining for Fact Checking in Knowledge GraphsCode0
Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks—0
Holographic Embeddings of Knowledge GraphsCode0
A Generative Model of Words and Relationships from Multiple Sources—0
Estimating network edge probabilities by neighborhood smoothingCode0
Aligning Knowledge and Text Embeddings by Entity Descriptions—0
Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction—0
Context-Dependent Knowledge Graph Embedding—0
Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors—0
Representing Text for Joint Embedding of Text and Knowledge Bases—0
Measuring Prerequisite Relations Among Concepts—0
Composing Relationships with Translations—0
Type-Constrained Representation Learning in Knowledge Graphs—0
Semantically Smooth Knowledge Graph Embedding—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