KGEM Meta-Review of Surveys and Benchmarks

This page contains a list of surveys and benchmarking studies for knowledge graph embedding model (KGEMs). It’s generated with GitHub Pages from GitHub logo pykeen/kgem-meta-review. Content on this site is available under the CC0 1.0 Universal license.

We define a survey as a paper that describes several KGEMs and a benchmark as one that presents systematic application of several KGEMs.

Contributing

You can contribute to this list in one of the following ways:

  1. Add a benchmark through the GitHub editor
  2. Add a survey through the GitHub editor

Benchmark Studies

Out-of-Vocabulary Entities in Link Prediction
Demir et al., 2021
arXiv GitHub Models Datasets

Identifies entities appearning in the testing/validation splits in three common benchmark datasets, provides an algorithm for fixing the splits, then presents an evaluation on the fixed datasets.

On Training Knowledge Graph Embedding Models
Mohamed et al., 2021
Models Datasets

A Survey on Knowledge Graph Embeddings for Link Prediction
Wang et al., 2021
Models Datasets

A Re-evaluation of Knowledge Graph Completion Methods
Sun et al., 2020
arXiv Models Datasets

You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings
Ruffinelli et al., 2020
GitHub Models Datasets

CODEX: A Comprehensive Knowledge Graph Completion Benchmark
Safavi et al., 2020
arXiv GitHub Models Datasets

Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes
Agibetov et al., 2020
arXiv Models Datasets

Knowledge Graph Embedding for Link Prediction: A Comparative Analysis
Rossi et al., 2020
arXiv GitHub Models Datasets

Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework
Ali et al., 2020
arXiv GitHub Models Datasets

Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study
Akrami et al., 2020
arXiv Models Datasets

JOINT EMBEDDING LEARNING OF EDUCATIONAL KNOWLEDGE GRAPHS
Yao et al., 2019
arXiv Models Datasets

PyTorch-BigGraph: A Large-scale Graph Embedding System
Lerer et al., 2019
arXiv Models Datasets

Surveys

A Survey of Knowledge Graph Embedding and Their Applications
Choudhary et al., 2021
arXiv Models

A Literature Review of Recent Graph Embedding Techniques for Biomedical Data
Chen et al., 2021
arXiv Models

A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Ji et al., 2020
arXiv Models

A Survey on Knowledge Graph Embedding: Approaches, Applications and Benchmarks
Dai et al., 2020

A survey of embedding models of entities and relationships for knowledge graph completion
Nguyen et al., 2020
arXiv Models Datasets

This survey contains an extensive compilation of results from previous papers

A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications
Cai et al., 2018
arXiv Models

Knowledge Graph Embedding: A Survey of Approaches and Applications
Wang et al., 2017

Complex and Holographic Embeddings of Knowledge Graphs: A Comparison
Trouillon et al., 2017
arXiv Models

A Review of Relational Machine Learning for Knowledge Graphs
Nickel et al., 2015
arXiv

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