%0 Journal Article
%T An Effective Method for Privacy Preserving Association Rule Mining<br>一种有效的隐私保护关联规则挖掘方法
%A ZHANG Peng
%A TONG Yun-Hai
%A TANG Shi-Wei
%A YANG Dong-Qing
%A MA Xiu-Li
%A <br>张鹏
%A 童云海
%A 唐世渭
%A 杨冬青
%A 马秀莉
%J 软件学报
%D 2006
%I 
%X Privacy preservation is one of the most important topics in data mining. The purpose is to discover accurate patterns without precise access to the original data. In order to improve the privacy preservation and mining accuracy, an effective method for privacy preserving association rule mining is presented in this paper. First, a new data preprocessing approach, Randomized Response with Partial Hiding (RRPH) is proposed. In this approach, the two privacy preserving strategies, data perturbation and query restriction, are combined to transform and hide the original data. Then, a privacy preserving association rule mining algorithm based on RRPH is presented. As shown in the theoretical analysis and the experimental results, privacy preserving association rule mining based on RRPH can achieve significant improvements in terms of privacy, accuracy, efficiency, and applicability.
%K privacy preservation
%K data mining
%K association rule
%K frequent itemset
%K randomized response<br>隐私保护
%K 数据挖掘
%K 关联规则
%K 频繁项集
%K 随机化回答
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=7D0A327C47D2F6D4&yid=37904DC365DD7266&vid=BCA2697F357F2001&iid=5D311CA918CA9A03&sid=961EEFF36C7AED30&eid=CC25DB91403D0902&journal_id=1000-9825&journal_name=软件学报&referenced_num=21&reference_num=16