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 1101–1150 of 1949 papers

TitleStatusHype
Representation Learning of Graphs Using Graph Convolutional Multilayer Networks Based on Motifs—0
Representation Learning of Reconstructed Graphs Using Random Walk Graph Convolutional Network—0
Representation Learning over Dynamic Graphs—0
ResVGAE: Going Deeper with Residual Modules for Link Prediction—0
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction—0
Representing Text for Joint Embedding of Text and Knowledge Bases—0
Adaptive Candidate Generation for Scalable Edge-discovery Tasks on Data Graphs—0
Causal Intervention for Measuring Confidence in Drug-Target Interaction Prediction—0
Resource of Wikipedias in 31 Languages Categorized into Fine-Grained Named Entities—0
Equipping SBMs with RBMs: An Explainable Approach for Analysis of Networks with Covariates—0
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning—0
Are Hyperbolic Representations in Graphs Created Equal?—0
A Relational-learning Perspective to Multi-label Chest X-ray Classification—0
RETRO: Relation Retrofitting For In-Database Machine Learning on Textual Data—0
A Relational Tucker Decomposition for Multi-Relational Link Prediction—0
DocGraphLM: Documental Graph Language Model for Information Extraction—0
Revisiting Graph Neural Networks for Link Prediction—0
Document Network Projection in Pretrained Word Embedding Space—0
Revisiting Knowledge Base Embedding as Tensor Decomposition—0
Revisiting Neighborhood-based Link Prediction for Collaborative Filtering—0
Bypassing Skip-Gram Negative Sampling: Dimension Regularization as a More Efficient Alternative for Graph Embeddings—0
Revisiting Virtual Nodes in Graph Neural Networks for Link Prediction—0
r-GAT: Relational Graph Attention Network for Multi-Relational Graphs—0
RGL: A Simple yet Effective Relation Graph Augmented Prompt-based Tuning Approach for Few-Shot Learning—0
NodeSig: Binary Node Embeddings via Random Walk Diffusion—0
RNNCTPs: A Neural Symbolic Reasoning Method Using Dynamic Knowledge Partitioning Technology—0
Robust Sequence Networked Submodular Maximization—0
Robust Training of Temporal GNNs using Nearest Neighbours based Hard Negatives—0
RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification—0
Does Link Prediction Help Detect Feature Interactions in Software Product Lines (SPLs)?—0
RotateCT: Knowledge Graph Embedding by Rotation and Coordinate Transformation in Complex Space—0
RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion—0
RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networks—0
Runtime Performances Benchmark for Knowledge Graph Embedding Methods—0
DOLORES: Deep Contextualized Knowledge Graph Embeddings—0
SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation—0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
Domain Generalization Deep Graph Transformation—0
Domain Representation for Knowledge Graph Embedding—0
SANGEA: Scalable and Attributed Network Generation—0
Scalability Matters: Overcoming Challenges in InstructGLM with Similarity-Degree-Based Sampling—0
Do Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach—0
Scalable Deep Generative Relational Models with High-Order Node Dependence—0
Scalable Deep Metric Learning on Attributed Graphs—0
Scalable Hierarchical Embeddings of Complex Networks—0
Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization—0
LPNL: Scalable Link Prediction with Large Language Models—0
Scalable Neural Theorem Proving on Knowledge Bases and Natural Language—0
Scalable Text and Link Analysis with Mixed-Topic Link Models—0
Scaling Knowledge Graph Embedding Models—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