A Hybrid Algorithm Combining Weighted and Hasht Apriori Algorithms in Map Reduce Model Using Eucalyptus Cloud Platform

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Abstract: Data mining performs a major role in data analysis which benefits enhancement of business. In modern era, distributed data mining becomes a major research area due to distributed computing. In distributed data mining data can be physically or virtually distributed that helps greatly in finding out interesting facts. Virtual distribution and distributed data mining gets its major impact on big data analysis with the help of cloud and grid computing. This research work performs data mining in a cloud environment using Eucalyptus platform with VMWare workstation and Hadoop platform. This work mines distributed data in a cloud environment using hybrid apriori association rule algorithm which combines the benefits of both hash-t and weighted apriori algorithms. Finally the work compares the performance with the existing implementation of weighted and hash-t algorithms

WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2880, Volume 14, 2015, Art. #38

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R. Sumithra, Sujni Paul, D. Ponmary Pushpa Latha, "A Hybrid Algorithm Combining Weighted and Hasht Apriori Algorithms in Map Reduce Model Using Eucalyptus Cloud Platform," WSEAS Transactions on Computers, vol. 14, pp. 382-388, 2015, DOI:
R. Sumithra, Sujni Paul, D. Ponmary Pushpa Latha. A Hybrid Algorithm Combining Weighted and Hasht Apriori Algorithms in Map Reduce Model Using Eucalyptus Cloud Platform. WSEAS Transactions on Computers. 2015;14:382-388.
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