Title :
MR-Apriori: Association Rules algorithm based on MapReduce
Author_Institution :
Inf. Sch., Ningbo City Coll. of vocational Technol., Ningbo, China
Abstract :
Traditional Association Rules algorithm has computing power shortage in dealing with massive datasets. In order to overcome these problems, a distributed association rules algorithm based on MapReduce programming model named MR-Apriori is proposed. In this paper, we introduce the MapReduce programming model of Hadoop platform and Apriori algorithm of data mining, propose the detailed procedure of MR-Apriori algorithm. Theoretical and experimental results show MR-Apriori algorithm make a sharp increase in efficiency.
Keywords :
cloud computing; data mining; distributed algorithms; Hadoop platform; MR-apriori; MapReduce programming model; cloud computing; data mining; distributed association rules algorithm; Algorithm design and analysis; Association rules; Cloud computing; Data models; Itemsets; Programming; Apriori algorithm; Association Rule; Data mining; Hadoop; MapReduce;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933531
