# pyRDF2Vec: A Python Implementation and Extension of RDF2Vec

arXiv: https://arxiv.org/abs/2205.02283 · HTML: https://mlsanity.com/paper/2205.02283/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 31 references that are in the map.
- First posted on arXiv 4 May 2022.

## Builds on (most cited first, 12 of 12)

- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Modeling Relational Data with Graph Convolutional Networks](https://mlsanity.com/paper/1703.06103/) (2017)
- [Learning Word Vectors for 157 Languages](https://mlsanity.com/paper/1802.06893/) (2018)
- [A Review of Relational Machine Learning for Knowledge Graphs](https://mlsanity.com/paper/1503.00759/) (2015)
- [OWL2Vec*: Embedding of OWL Ontologies](https://mlsanity.com/paper/2009.14654/) (2020)
- [A Survey of Knowledge Graph Embedding and Their Applications](https://mlsanity.com/paper/2107.07842/) (2021)
- [R-GCN: The R Could Stand for Random](https://mlsanity.com/paper/2203.02424/) (2022)
- [Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs](https://mlsanity.com/paper/2009.04404/) (2020)
- [Putting RDF2vec in Order](https://mlsanity.com/paper/2108.05280/) (2021)
- [Towards Exploiting Implicit Human Feedback for Improving RDF2vec Embeddings](https://mlsanity.com/paper/2004.04423/) (2020)
- [Graph Node Embeddings using Domain-Aware Biased Random Walks](https://mlsanity.com/paper/1908.02947/) (2019)
- [More is not Always Better: The Negative Impact of A-box Materialization on RDF2vec Knowledge Graph Embeddings](https://mlsanity.com/paper/2009.00318/) (2020)

## Built on by (most cited first, 8 of 8)

- [Universal Preprocessing Operators for Embedding Knowledge Graphs with Literals](https://mlsanity.com/paper/2309.03023/) (2023)
- [Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks](https://mlsanity.com/paper/2303.01140/) (2023)
- [Leveraging Wikidata's edit history in knowledge graph refinement tasks](https://mlsanity.com/paper/2210.15495/) (2022)
- [Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts](https://mlsanity.com/paper/2402.05536/) (2024)
- [OWL2Vec4OA: Tailoring Knowledge Graph Embeddings for Ontology Alignment](https://mlsanity.com/paper/2408.06310/) (2024)
- [An Embedding-based Approach to Inconsistency-tolerant Reasoning with Inconsistent Ontologies](https://mlsanity.com/paper/2304.01664/) (2023)
- [PDPK: A Framework to Synthesise Process Data and Corresponding Procedural Knowledge for Manufacturing](https://mlsanity.com/paper/2308.08371/) (2023)
- [gpuRDF2vec -- Scalable GPU-based RDF2vec](https://mlsanity.com/paper/2508.01073/) (2025)

## Abstract (arXiv)

This paper introduces pyRDF2Vec, a Python software package that reimplements the well-known RDF2Vec algorithm along with several of its extensions. By making the algorithm available in the most popular data science language, and by bundling all extensions into a single place, the use of RDF2Vec is simplified for data scientists. The package is released under a MIT license and structured in such a way to foster further research into sampling, walking, and embedding strategies, which are vital components of the RDF2Vec algorithm. Several optimisations have been implemented in textttpyRDF2Vec that allow for more efficient walk extraction than the original algorithm. Furthermore, best practices in terms of code styling, testing, and documentation were applied such that the package is future-proof as well as to facilitate external contributions.