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 15011550 of 1949 papers

TitleStatusHype
Which way? Direction-Aware Attributed Graph EmbeddingCode0
How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction0
Graph Neighborhood Attentive PoolingCode0
Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data0
Graph Ordering: Towards the Optimal by Learning0
ExEm: Expert Embedding using dominating set theory with deep learning approachesCode0
Document Network Projection in Pretrained Word Embedding Space0
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural NetworkCode0
Social Science Guided Feature Engineering: A Novel Approach to Signed Link Analysis0
Knowledge Graph Embedding via Graph Attenuated Attention Networks0
Clustering as an Evaluation Protocol for Knowledge Embedding Representation of Categorised Multi-relational Data in the Clinical Domain0
Neural Subgraph Isomorphism CountingCode0
Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized DataCode0
Meta-Graph: Few Shot Link Prediction via Meta LearningCode0
Bridging the Gap between Community and Node Representations: Graph Embedding via Community DetectionCode0
Fast Computation of Katz Index for Efficient Processing of Link Prediction Queries0
Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks0
OpenBioLink: A benchmarking framework for large-scale biomedical link predictionCode0
Sparse Graph Attention NetworksCode0
Gaussian Embedding of Large-scale Attributed GraphsCode0
JNET: Learning User Representations via Joint Network Embedding and Topic EmbeddingCode0
Pretrain-KGEs: Learning Knowledge Representation from Pretrained Models for Knowledge Graph Embeddings0
Cross-Domain Recommendation via Preference Propagation GraphNet0
Scalable Deep Generative Relational Model with High-Order Node DependenceCode0
Outliers Detection in Networks with Missing Links0
RETRO: Relation Retrofitting For In-Database Machine Learning on Textual Data0
Generative Temporal Link Prediction via Self-tokenized Sequence Modeling0
Network Embedding: An Overview0
Effective Decoding in Graph Auto-Encoder using Triadic Closure0
Time-aware Gradient Attack on Dynamic Network Link Prediction0
Exponential Family Graph Embeddings0
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph RepresentationsCode0
Tensor Decomposition with Relational Constraints for Predicting Multiple Types of MicroRNA-disease AssociationsCode0
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language RepresentationCode0
Decompressing Knowledge Graph Representations for Link PredictionCode0
Equipping SBMs with RBMs: An Explainable Approach for Analysis of Networks with Covariates0
A Re-evaluation of Knowledge Graph Completion MethodsCode0
Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding0
Neural Graph Embedding Methods for Natural Language ProcessingCode0
Relation Adversarial Network for Low Resource Knowledge Graph Completion0
SENSE: Semantically Enhanced Node Sequence Embedding0
Hyper-SAGNN: a self-attention based graph neural network for hypergraphsCode0
CoKE: Contextualized Knowledge Graph EmbeddingCode0
GraphAIR: Graph Representation Learning with Neighborhood Aggregation and InteractionCode0
Dynamic Graph Embedding via LSTM History Tracking0
Scalable Deep Generative Relational Models with High-Order Node Dependence0
InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature InteractionsCode0
CaRe: Open Knowledge Graph Embeddings0
DRUM: End-To-End Differentiable Rule Mining On Knowledge GraphsCode0
A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?0
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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
8ComplEx-N3 (reciprocal)Hits@100.96Unverified
9MEI (small)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