DocumentCode
3301671
Title
Privacy preserving high utility mining based on genetic algorithms
Author
Chun-Wei Lin ; Tzung-Pei Hong ; Jia-Wei Wong ; Guo-Cheng Lan
Author_Institution
Innovative Inf. Ind. Res. Center, Harbin Inst. of Technol., Shenzhen, China
fYear
2013
fDate
13-15 Dec. 2013
Firstpage
191
Lastpage
195
Abstract
In this paper, a GA-based privacy-preserving utility mining method is proposed to delete appropriate transactions for hiding sensitive high utility itemsets from a database. The downward closure property and the pre-large concepts are adopted in the proposed algorithm to reduce the cost of rescanning databases. Experiments are also conducted to evaluate the performance of the proposed approach in execution time and the amount of side-effects.
Keywords
data mining; data privacy; database management systems; genetic algorithms; GA-based privacy-preserving utility mining method; downward closure property; execution time; genetic algorithms; pre-large concepts; Biological cells; Data mining; Genetic algorithms; Itemsets; Sociology; Statistics; evolutionary computation; genetic algorithm; pre-large concept; privacy preserving; utility mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2013 IEEE International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/GrC.2013.6740406
Filename
6740406
Link To Document