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 :
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