Title :
A Randomization Approach to Mining Sequential Pattern with Privacy Preserving
Author :
Ouyang, Weimin ; Huang, Qinhua ; Xin, Hongliang
Author_Institution :
Modern Educ. Technol. Center, Shanghai Univ. of Political Sci. & Law, Shanghai
Abstract :
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.
Keywords :
data mining; data privacy; privacy-preserving data mining; randomization approach; sequential pattern; Classification tree analysis; Computational intelligence; Computer science education; Data mining; Databases; Decision trees; Design engineering; Educational technology; Null value; Privacy;
Conference_Titel :
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3311-7
DOI :
10.1109/ISCID.2008.111