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 901–925 of 1949 papers

TitleStatusHype
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction—0
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization—0
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs—0
Knowledge Graph Embedding with Multiple Relation Projections—0
Improving Link Prediction in Social Networks Using Local and Global Features: A Clustering-based Approach—0
Knowledge Graph Reasoning Based on Attention GCN—0
Improving Neural Knowledge Base Completion with Cross-Lingual Projections—0
Improving Node Representation by Boosting Target-Aware Contrastive Loss—0
Document Network Projection in Pretrained Word Embedding Space—0
Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks—0
Knowledge Graphs and Knowledge Networks: The Story in Brief—0
Community Aware Random Walk for Network Embedding—0
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction—0
Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions—0
Incorporating GAN for Negative Sampling in Knowledge Representation Learning—0
DOLORES: Deep Contextualized Knowledge Graph Embeddings—0
Knowledge Graph Embeddings in Geometric Algebras—0
Incremental Learning on Growing Graphs—0
Pre-Trained Models for Heterogeneous Information Networks—0
Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention—0
Exploring Graph Neural Networks for Indian Legal Judgment Prediction—0
Domain Representation for Knowledge Graph Embedding—0
Exploring Effects of Random Walk Based Minibatch Selection Policy on Knowledge Graph Completion—0
Do Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach—0
Combinatorial Scientific Discovery: Finding New Concept Combinations Beyond Link Prediction—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