DocumentCode
3129107
Title
Multi-dimension association rule mining based on Adaptive Genetic Algorithm
Author
Wang, Min ; Zou, Qin ; Liu, Caihui
Author_Institution
Sch. of mathematic & Comput. Sci., Gannan Normal Univ., Ganzhou, China
Volume
2
fYear
2011
fDate
4-7 Aug. 2011
Firstpage
150
Lastpage
153
Abstract
This paper proposes a method of mining multi-dimension association rule based on the Adaptive Genetic Algorithm (AGA) with crossover matrix and mutation matrix. In this association rule mining system, selection, mutation, and crossover are all parameter-free in evolution process. Results show that: combined with the adaptive genetic algorithm, the precision and efficiency of mining association rules is improved.
Keywords
data mining; genetic algorithms; adaptive genetic algorithm; crossover matrix; multidimension association rule mining; mutation matrix; Association rules; Biological cells; Genetic algorithms; Indexes; Itemsets; Adaptive Genetic Algorithm; Crossover Matrix; Multi-dimension Association Rule; Mutation Matrix;
fLanguage
English
Publisher
ieee
Conference_Titel
Uncertainty Reasoning and Knowledge Engineering (URKE), 2011 International Conference on
Conference_Location
Bali
Print_ISBN
978-1-4244-9985-4
Electronic_ISBN
978-1-4244-9984-7
Type
conf
DOI
10.1109/URKE.2011.6007931
Filename
6007931
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