DocumentCode
568151
Title
An improved association rule algorithm based on Itemset Matrix and Cluster Matrix
Author
Jian, Peng ; Xiao-ling, Wang
Author_Institution
Dept. of Comput. Sci. & Technol., Hunan Inst. of Humanities, Loudi, China
fYear
2012
fDate
14-17 July 2012
Firstpage
834
Lastpage
837
Abstract
Through the analysis of the method of association rules, an improved algorithm in association rules based on Itemset Matrix(ISM) and Cluster Matrix(CMa) is put forward. The algorithm can get the new frequent itemsets just through scanning the updated data once again, when the database and the minimum support degree are changed. Studies and analysis of the algorithm show that it just need to scan the database once, so it has the virtues in high-speed producing frequent k-itemsets and less time cost. And it improves the efficiency of the association mining, can fulfill the request of shortening the time of mining.
Keywords
data mining; matrix algebra; pattern clustering; CMa; ISM; association mining efficiency improvement; cluster matrix; frequent k-itemsets mining; improved association rule algorithm; itemset matrix; Algorithm design and analysis; Association rules; Clustering algorithms; Itemsets; Vectors; Cluster Matrixes(CMa); Itemset Matrixes(ISM); association rules; association vector;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science & Education (ICCSE), 2012 7th International Conference on
Conference_Location
Melbourne, VIC
Print_ISBN
978-1-4673-0241-8
Type
conf
DOI
10.1109/ICCSE.2012.6295199
Filename
6295199
Link To Document