Database Paper Browser

Back to papers

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
8885
Venue
VLDB
Year
2002
Pagerank
0.00020147576
Overall Rank
559 | 96.12%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank Cited Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Semantically Similar Papers