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Publishing Set-Valued Data via Differential Privacy

Summary: Differentially private release of set-valued data via taxonomy trees and a top-down partitioning with linear scaling. Shows epsilon-delta usefulness for counting queries; preserves utility for counting and frequent itemsets; validated on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10173
Venue
VLDB
Year
2011
Pagerank
7.5578714e-05
Overall Rank
3,103 | 78.44%
DOI
-

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