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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)

Paper ID
h337c9d47fca0bbcb
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
11,014 | 25.95%
DOI
10.14778/3827998.3828127

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Authors

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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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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