A survey of transaction dada anonymous publication

Lan Sun, Yilei Wang, Yingjie Wu
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引用次数: 3

Abstract

Transaction data contain a large amount of information of individuals and entities. Publication of these data can provide important resources for researching such as association rule mining, recommendation systems and user behavior prediction ect. But on the other hand, it will compromise individual privacy. Recently, many works focus on privacy preserving transaction data publishing, especially on anonymous publishing. In this paper, we will systematically summarize and evaluate different anonymous approaches for transactional data publication.
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交易数据匿名发表调查
交易数据包含了大量的个人和实体信息。这些数据的发布可以为关联规则挖掘、推荐系统和用户行为预测等研究提供重要的资源。但另一方面,它会损害个人隐私。近年来,许多研究都集中在保护隐私的交易数据发布,特别是匿名发布方面。在本文中,我们将系统地总结和评估交易数据发布的不同匿名方法。
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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