privJedAI: A Unified Open-Source Pipeline for Privacy-Preserving Record Linkage
Summary: privJedAI is an open-source Python library implementing a broad, composable Filtering–Verification toolkit for privacy-preserving record linkage. It enables intuitive end-to-end pipeline construction and benchmarking across effectiveness–efficiency trade-offs, addressing the narrow scope of prior systems. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Lefteris Stetsikas (National and Kapodistrian University of Athens)
- 2. Dimitrios Karapiperis (International Hellenic University)
- 3. George Papadakis (National and Kapodistrian University of Athens)
- 4. Manolis Koubarakis (National and Kapodistrian University of Athens)
BibTeX Citation
@article{stetsikas_vldb26,
title = {{privJedAI: A Unified Open-Source Pipeline for Privacy-Preserving Record Linkage}},
author = {Stetsikas, Lefteris and Karapiperis, Dimitrios and Papadakis, George and Koubarakis, Manolis},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4806--4809},
doi = {10.14778/3827998.3828127},
url = {https://doi.org/10.14778/3827998.3828127},
year = {2026}
}
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Outgoing Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 6,344 | PRIMAT: A Toolbox for Fast Privacy-preserving Matching | 2019 | VLDB | 5.8092399e-05 |
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