DocumentCode
2096414
Title
The Study on the Application of Data Mining Based on Association Rules
Author
Fang, Luo ; Qizhi, Qiu
Author_Institution
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China
fYear
2012
fDate
11-13 May 2012
Firstpage
477
Lastpage
480
Abstract
Association rule mining finds interesting association or correlation relationships among a large set of data items, which is an important task of data mining. Meanwhile, Apriori is an influential algorithm for mining frequent itemsets for Boolean association rules. Firstly, the concept and the effect of association rules are introduced and the classic algorithms of association rule are analyzed. In Apriori algorithm, most time is consumed for scanning the database repeatedly. Therefore, the methods are presented about improving the Apriori algorithm efficiency, which reduces a lot of time of scanning database and shortens the computation time of the algorithm. Furthermore, several typical applications of association rules in Market-Basket Analysis are given.
Keywords
Boolean functions; data mining; Apriori algorithm; Boolean association rules; data mining; frequent itemsets mining; market-basket analysis; Algorithm design and analysis; Association rules; Data warehouses; Itemsets; Wireless application protocol; Apriori algorithm; Association rule; Candidate itemset; Data mining; Frequent itemset;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Systems and Network Technologies (CSNT), 2012 International Conference on
Conference_Location
Rajkot
Print_ISBN
978-1-4673-1538-8
Type
conf
DOI
10.1109/CSNT.2012.108
Filename
6200681
Link To Document