LinkIT: Privacy Preserving Record Linkage and Integration via Transformations
Summary: Open-source LinkIT for privacy-preserving record linkage and integration via data transformations; usable with FRIL or as a standalone string-linker. Introduces a novel embedding using frequent variable-length grams with differential privacy and a personalized linkage threshold, offering stronger privacy and scalability with utility similar to state-of-the-art secure transformations. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Luca Bonomi (Emory University)
- 2. Li Xiong (Emory University)
- 3. James J. Lu (Emory University)
BibTeX Citation
@inproceedings{bonomi_sigmod13,
title = {{LinkIT: Privacy Preserving Record Linkage and Integration via Transformations}},
author = {Bonomi, Luca and Xiong, Li and Lu, James J.},
series = {{SIGMOD} '13},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2463676.2465259},
url = {https://dl.acm.org/doi/10.1145/2463676.2465259},
year = {2013}
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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 |
|---|---|---|---|---|
| 2,103 | Cost-Based Variable-Length-Gram Selection for String Collections to Support Approximate Queries Efficiently | 2008 | SIGMOD | 9.1621686e-05 |
| 4,913 | Privacy Preserving Schema and Data Matching | 2007 | SIGMOD | 6.4479393e-05 |
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