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A Randomization Approach to Mining Sequential Pattern with Privacy Preserving

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3 Author(s)
Weimin Ouyang ; Modern Educ. Technol. Center, Shanghai Univ. of Political Sci. & Law, Shanghai ; Qinhua Huang ; Hongliang Xin

Data mining is to discover previously unknown, potentially useful and nontrivial knowledge, patterns or rules. Because databases may have some sensitive information that should not to be leaked out, we should study how to make data mining without leaking sensitive information, i.e., privacy-preserving data mining. We propose a randomization approach for privacy-preserving mining of sequential patterns in this paper.

Published in:

Computational Intelligence and Design, 2008. ISCID '08. International Symposium on  (Volume:2 )

Date of Conference:

17-18 Oct. 2008