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Maintaining Data Privacy in Association Rule Mining

Summary: Proposes a probabilistic data-distortion scheme to protect privacy in association rule mining. Shows privacy preserved without sacrificing accuracy, validated on real and synthetic data, highlighting the utility-privacy trade-off in privacy-preserving ARM. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9076
Venue
VLDB
Year
2002
Pagerank
0.00011627624
Overall Rank
1,217 | 91.66%
DOI
10.1016/B978-155860869-6/50066-4

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{rizvi_vldb02,
        title = {{Maintaining Data Privacy in Association Rule Mining}},
        author = {Rizvi, Shariq J. and Haritsa, Jayant R.},
        journal = {PVLDB},
        series = {{VLDB} '02},
        doi = {10.1016/B978-155860869-6/50066-4},
        url = {https://doi.org/10.1016/B978-155860869-6/50066-4},
        year = {2002}
}

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