文章基本信息

标题：Privacy Preserving Clustering in Data Mining Using VQ Code Book Generation
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作者：D.Aruna Kumari ; Rajasekhara Rao ; M.Suman 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2012
卷号：2
期号：4
页码：317-323
DOI：10.5121/csit.2012.2430
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Huge Volumes of detailed personal data is regularly collected and analyzed by applications using data mining, sharing of these data is beneficial to the application users. On one hand it is an important asset to business organizations and governments for decision making at the same time analysing such data opens treats to privacy if not done properly. This paper aims to reveal the information by protecting sensitive data. We are using Vector quantization technique for preserving privacy. Quantization will be performed on training data samples it will produce transformed data set. This transformed data set does not reveal the original data. Hence privacy is preserved.
关键词：Vector quantization; code book generation; privacy preserving data mining ;k-means clustering.