An approach to outsourcing data mining tasks while protecting business intelligence and customer privacy

被引:0
|
作者
Qiu, Ling [1 ]
Li, Yingjiu
Wu, Xintao
机构
[1] James Cook Univ N Queensland, Sch Math Phys & IT, Townsville, Qld 4811, Australia
[2] Singapore Management Univ, Sch Informat Syst, Singapore 178902, Singapore
[3] Univ N Carolina, Dept Comp Sci, Charlotte, NC 28223 USA
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Data mining is playing an important role in decision making. It is beneficial to outsource data mining tasks if an organization does not have required expertise in-house. However, the organization may lose business intelligence and customer privacy during this outsourcing process. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules while protecting their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off storage requirements.
引用
收藏
页码:551 / 555
页数:5
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