Privacy preservation algorithm in data mining for CRM systems

Shashidhar Virupaksha, G. Sahoo, A. Vasudevan
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引用次数: 5

Abstract

Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy protection algorithms which ensure privacy and protect data. These algorithms preserve privacy but data mining results significantly. In this paper we propose a clustering based noise addition that not only preserves privacy but also ensures effective data mining. Data characteristics are identified using clustering technique and noise is added within the clusters thus retaining the data characteristics.
CRM系统数据挖掘中的隐私保护算法
组织拥有庞大的客户群,因此他们使用数据挖掘工具来研究他们的客户。然而,在这一过程中也可能获得有关个人的敏感信息。因此,必须保护用于数据挖掘的数据。有一些隐私保护算法可以保证隐私和保护数据。这些算法保护隐私,但数据挖掘效果显著。本文提出了一种基于聚类的噪声添加方法,既保护了隐私,又保证了数据挖掘的有效性。采用聚类技术识别数据特征,并在聚类中加入噪声,从而保留数据特征。
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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