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RDFFrames: Knowledge Graph Access for Machine Learning Tools

Summary: RDFFrames provides a Python-centric, traversal-based data extraction bridge from RDF stores to ML workflows, translating imperative calls into compact SPARQL queries. It delivers tabular results with DB performance, addressing the mismatch between ML tooling and SPARQL's graph-pattern interface. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12343
Venue
VLDB
Year
2020
Pagerank
5.093636e-05
Overall Rank
11,807 | 19.00%
DOI
10.14778/3415478.3415501

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Authors

BibTeX Citation

@article{mohamed_vldb20,
        title = {{RDFFrames: Knowledge Graph Access for Machine Learning Tools}},
        author = {Mohamed, Aisha and Abuoda, Ghadeer and Ghanem, Abdurrahman and Kaoudi, Zoi and Aboulnaga, Ashraf},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {12},
        pages = {2889--2892},
        doi = {10.14778/3415478.3415501},
        url = {https://doi.org/10.14778/3415478.3415501},
        year = {2020}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
110 Extensible/Rule Based Query Rewrite Optimization in Starburst 1992 SIGMOD 0.0003309592
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