An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy

Ling Qiu, Yingjiu Li, Xintao Wu
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引用次数: 15

Abstract

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
在保护商业智能和客户隐私的同时外包数据挖掘任务的方法
数据挖掘在决策中起着重要的作用。如果组织内部没有所需的专业知识,那么将数据挖掘任务外包是有益的。然而,在此外包过程中,组织可能会丢失业务智能和客户隐私。在本文中,我们提出了一个基于Bloom过滤器的解决方案,使组织能够外包挖掘关联规则的任务,同时保护他们的商业智能和客户隐私。我们的方法可以通过权衡存储需求来实现数据挖掘的高精度
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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