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Association Rule Mining in Big Data: A New Perspective

S. Charles, N. Aarthi

Abstract


An association rule is a remarkable approach to pull out frequent items from Big Data. This article gives a theoretical overview of association rule-making, Hadoop and MapReduce implementation of the association rule is performed on the different dataset given by the researcher. Further, the association rule based techniques are discussed and the efficiency of algorithms is compared in terms of scale-up, speed up and sizeup measures in big data. The goal of an association is not expected from a random sampling of all possibilities. It might just find relations of items that happen together. The performance of algorithms analyzed with respect to speed up, size up and scale up factors related to the prediction of big data analytics. However, the paper cannot boast to be a complete review of all the research work in an area. In this paper, makeup and offer an appraisal of the work carried out and done by researchers using association rule in Big Data.


Keywords


Big Data, MapReduce, Association Rule, Machine Learning, Hadoop, A-Priori, Size Up, Scale Up Speed Up.

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