文章基本信息

标题：Privacy Preservation Decision Tree Based On Data Set Complementation
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作者：MADHUSMITA SAHU ; DEBASIS GOUNTIA ; NEELAMANI SAMAL 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2013
卷号：1
期号：2
出版社：S&S Publications
摘要：Privacy preservation in data mining has been a popular and an important research area for more than a decadedue to its vast spectrum of applications. A new class of data mining method called privacy preserving data miningalgorithm has been developed. The aim of this algorithm is to protect the sensitive information in data from the largeamount of data set. The privacy preservation of data set can be expressed in the form of decision tree, cluster or associationrule. This paper proposes a privacy preservation based on data set complement algorithms which store the information ofthe real dataset. So that the private data can be safe from the unauthorized party, if some portion of the data can be lost,then we can reconstructed the original data set from the unrealized dataset and the perturbing data set.
关键词：Data mining; classification; machine learning; privacy preservation