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On Differentially Private Frequent Itemset Mining

Summary: Shows that DP frequent-itemset mining suffers sharply from long transactions, motivating transaction truncation to balance truncation and privacy noise. The resulting classical threshold-mining algorithm outperforms top-k methods in F-score except for small k. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10879
Venue
VLDB
Year
2013
Pagerank
8.6866148e-05
Overall Rank
2,366 | 83.77%
DOI
10.14778/2428536.2428539

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zeng_vldb13,
        title = {{On Differentially Private Frequent Itemset Mining}},
        author = {Zeng, Chen and Naughton, Jeffrey F. and Cai, Jin-Yi},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {1},
        doi = {10.14778/2428536.2428539},
        url = {https://doi.org/10.14778/2428536.2428539},
        year = {2013}
}

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