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Article Information:
Apriori Association Rule Algorithms using VMware Environment
R. Sumithra, Sujni Paul and D. Ponmary Pushpa Latha
Corresponding Author: R. Sumithra
Submitted: January 20, 2014
Accepted: February 15, 2014
Published: July 10, 2014 |
Abstract:
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The aim of this study is to carry out a research in distributed data mining using cloud platform. Distributed Data mining becomes a vital component of big data analytics due to the development of network and distributed technology. Map-reduce hadoop framework is a very familiar concept in big data analytics. Association rule algorithm is one of the popular data mining techniques which finds the relationships between different transactions. A work has been executed using weighted apriori and hash T apriori algorithms for association rule mining on a map reduce hadoop framework using a retail data set of transactions. This study describes the above concepts, explains the experiment carried out with retail data set on a VMW are environment and compares the performances of weighted apriori and hash-T apriori algorithms in terms of memory and time.
Key words: Association rules, cloud mining, hadoop, hash-T, map-reduce, W-apriori,
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Cite this Reference:
R. Sumithra, Sujni Paul and D. Ponmary Pushpa Latha, . Apriori Association Rule Algorithms using VMware Environment. Research Journal of Applied Sciences, Engineering and Technology, (2): 160-166.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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