DocumentCode
3111652
Title
A Novel Genetic Algorithm Based on Image Databases for Mining Association Rules
Author
Dai, Shangping ; Gao, Li ; Zhu, Qiang ; Zhu, Changwu
Author_Institution
Hua Zhong Normal Univ., Wuhan
fYear
2007
fDate
11-13 July 2007
Firstpage
977
Lastpage
980
Abstract
Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. Mining encompasses various algorithms such as clustering, classification, and association rule mining. In this paper we take advantage of the genetic algorithm (GA) designed specifically for discovering association rules. We propose a novel spatial mining algorithm, called ARMNGA(association rules mining in novel genetic algorithm), Compared to the algorithm in [Agrawal R, et al., Mining association rules between sets of items in large databases, 1993], the ARMNGA algorithm avoids generating impossible candidates, and therefore is more efficient in terms of the execution time.
Keywords
data mining; genetic algorithms; visual databases; data mining technology; genetic algorithm; image databases; mining association rules; Algorithm design and analysis; Association rules; Biological cells; Clustering algorithms; Computer science; Data mining; Frequency measurement; Genetic algorithms; Genetic mutations; Image databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on
Conference_Location
Melbourne, Qld.
Print_ISBN
0-7695-2841-4
Type
conf
DOI
10.1109/ICIS.2007.40
Filename
4276510
Link To Document