Papers › RDF2Vec: RDF Graph Embeddings and Their Applications
RDF2Vec: RDF Graph Embeddings and Their Applications
Petar Ristoski, Jessica Rosati, Tommaso Di Noia, Renato De Leone, Heiko Paulheim
Linked Open Data has been recognized as a valuable source for background information in many data mining and information retrieval tasks. However, most of the existing tools require features in propositional form, i.e., a vector of nominal or numerical features associated with an instance, while Linked Open Data sources are graphs by nature. In this paper, we present RDF2Vec, an approach that uses language modeling approaches for unsupervised feature extraction from sequences of words, and adapts them to RDF graphs.We generate sequences by leveraging local information from graph sub-structures, harvested by Weisfeiler-Lehman Subtree RDF Graph Kernels and graph walks, and learn latent numerical representations of entities in RDF graphs.We evaluate our approach on three different tasks: (i) standard machine learning tasks, (ii) entity and document modeling, and (iii) content-based recommender systems. The evaluation shows that the proposed entity embeddings outperform existing techniques, and that pre-computed feature vector representations of general knowledge graphs such as DBpedia and Wikidata can be easily reused for different tasks.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Node Classification | AIFB | RDF2Vec+SVM | Accuracy | 88.88 | #6 of 7 | Archive leaderboard | report |
| Node Classification | AM | RDF2Vec+SVM | Accuracy | 88.33 | #5 of 8 | Archive leaderboard | report |
| Node Classification | BGS | RDF2Vec+SVM | Accuracy | 87.24 | #3 of 7 | Archive leaderboard | report |
| Node Classification | MUTAG | RDF2Vec+SVM | Accuracy | 67.20 | #6 of 6 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Introduced by this paper: RDF2Vec
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