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Privacy-Preserving Data Mining

Summary: Privacy-preserving data mining: build models from perturbed training data without access to exact individual records. Introduces a reconstruction procedure to recover the original-data distributions, enabling decision-tree classifiers with accuracy close to that achieved with original data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3267
Venue
SIGMOD
Year
2000
Pagerank
0.0003804755
Overall Rank
70 | 99.53%
DOI
10.1145/342009.335438

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{agrawal_sigmod00,
        title = {{Privacy-Preserving Data Mining}},
        author = {Agrawal, Rakesh and Srikant, Ramakrishnan},
        series = {{SIGMOD} '00},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/342009.335438},
        url = {https://dl.acm.org/doi/10.1145/342009.335438},
        year = {2000}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 51 citing papers.

Rank Citing Paper Year Venue Pagerank
12,809 Privacy in Data Systems 2003 PODS 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
249 Statistical Databases: Characteristics, Problems, and Some Solutions 1982 VLDB 0.00023275528
440 An Interval Classifier for Database Mining Applications 1992 VLDB 0.00018409145
952 Recovering Information from Summary Data 1997 VLDB 0.00013010681
1,081 A study on the protection of statistical data bases 1977 SIGMOD 0.00012257715
1,183 An Analytic Approach to Statistical Databases 1983 VLDB 0.00011778053
1,485 SPRINT: A Scalable Parallel Classifier for Data Mining 1996 VLDB 0.00010628998
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