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Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response
Joint Authors
Sun, Chongjing
Fu, Yan
Zhou, Junlin
Gao, Hui
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-30
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data.
There are increasing concerns about the privacy problem in the frequent itemset mining.
Some works have been proposed to handle this kind of problem.
In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection.
To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique.
By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level.
Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy.
American Psychological Association (APA)
Sun, Chongjing& Fu, Yan& Zhou, Junlin& Gao, Hui. 2014. Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1050616
Modern Language Association (MLA)
Sun, Chongjing…[et al.]. Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response. The Scientific World Journal No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1050616
American Medical Association (AMA)
Sun, Chongjing& Fu, Yan& Zhou, Junlin& Gao, Hui. Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1050616
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050616