DocumentCode
2826810
Title
Quantitative Association Rules Mining Algorithm Based on Matrix
Author
Liu, Huizhen ; Dai, Shangping ; Jiang, Hong
Author_Institution
Dept. of Comput. Sci., Huazhong Normal Univ., Wuhan, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
How to improve the efficiency of discovering the frequent item sets is a major problem in mining association rules. This paper analysised the idea and performance of the general quantitative association rules algorithm ,and put forward a quantitative association rules mining algorithm based on matrix, the new algorithm firstly transformed quantitative database into Boolean matrix ,then used boolean "and" operation to generate frequent item sets on matrix vector .It effectively solved the bottleneck of Apriori algorithm which iteratively produced frequent item sets in the general quantitative association rules algorithm . The results of experiments and analysis showed that the new algorithm effectively improved the efficiency of mining quantitative association rules.
Keywords
Boolean algebra; data mining; matrix algebra; Boolean matrix; iteratively produced frequent item sets; matrix vector; quantitative association rules mining algorithm; Algorithm design and analysis; Artificial intelligence; Association rules; Computer science; Data mining; Iterative algorithms; Machine learning algorithms; Performance analysis; Relational databases; Transaction databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5363896
Filename
5363896
Link To Document