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
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;
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
DOI :
10.1109/URKE.2011.6007931
