Title :
An efficient filtration approach for mining association rules
Author :
Goyal, Lalit Mohan ; Beg, M.M.S.
Author_Institution :
Dept. of Comput. Eng., Jamia Millia Islamia, New Delhi, India
Abstract :
Association rule mining (ARM) is a well-researched domain in the field of data mining. It is seen as a problem of predicting customers purchasing behavior, popularly known as “Market Basket Analysis”. This problem can be solved by using Apriori algorithm which is majorly 3-steps (Joining, Pruning and Verification) process. In this paper, an alternate to Apriori algorithm´s pruning step is proposed. This alternative is depicted as a filtration step.
Keywords :
consumer behaviour; data mining; purchasing; ARM; apriori algorithm; association rule mining; customer purchasing behavior prediction; data mining; filtration approach; joining process; market basket analysis; pruning process; verification process; Association rules; Computers; Correlation; Filtration; Itemsets; ARM (Association Rule Mining); Apriori algorithm; Data mining; pruning;
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-93-80544-10-6
DOI :
10.1109/IndiaCom.2014.6828124
