Pykg2vec: A Python Library for Knowledge Graph Embedding
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Abstract (arXiv)
Pykg2vec is an open-source Python library for learning the representations of the entities and relations in knowledge graphs. Pykg2vec's flexible and modular software architecture currently implements 16 state-of-the-art knowledge graph embedding algorithms, and is designed to easily incorporate new algorithms. The goal of pykg2vec is to provide a practical and educational platform to accelerate research in knowledge graph representation learning. Pykg2vec is built on top of TensorFlow and Python's multiprocessing framework and provides modules for batch generation, Bayesian hyperparameter optimization, mean rank evaluation, embedding, and result visualization. Pykg2vec is released under the MIT License and is also available in the Python Package Index (PyPI). The source code of pykg2vec is available at https://github.com/Sujit-O/pykg2vec.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jun 2019.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 3; 2024: 0; 2025: 2.
9 papers.
- 2023RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understandingcited by 17
- 2022NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphscited by 8
- 2022μKG: A Library for Multi-source Knowledge Graph Embeddings and Applicationscited by 4
- 2021A Novel Word Sense Disambiguation Approach Using WordNet Knowledge Graphcited by 2
- 2025DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusioncited by 2
- 2023Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods?cited by 1
- 2023NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learningcited by 1
- 2021Causal Discovery in Knowledge Graphs by Exploiting Asymmetric Properties of Non-Gaussian Distributionscited by 0
- 2025SparseTransX: Efficient Training of Translation-Based Knowledge Graph Embeddings Using Sparse Matrix Operationscited by 0
- 2025DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion15 Jul 2025
- 2025SparseTransX: Efficient Training of Translation-Based Knowledge Graph Embeddings Using Sparse Matrix Operations24 Feb 2025
- 2023NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learning28 Apr 2023
- 2023RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understanding17 Apr 2023
- 2023Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods?30 Jan 2023
- 2022μKG: A Library for Multi-source Knowledge Graph Embeddings and Applications23 Jul 2022
- 2022NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs25 Feb 2022
- 2021Causal Discovery in Knowledge Graphs by Exploiting Asymmetric Properties of Non-Gaussian Distributions2 Jun 2021
- 2021A Novel Word Sense Disambiguation Approach Using WordNet Knowledge Graph8 Jan 2021