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 :
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