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An Enhancement of the MapReduce Apriori Algorithm Using Vertical Data Layout and Set Theory Concept of Intersection

  • S. Dhanya
  • M. Vysaakan
  • A. S. Mahesh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 385)

Abstract

The process of Association Rule Generation is an important task in Data Mining. It is widely used for the Market Basket Analysis. The data that is used for the generation of Association Rules is usually distributed and complex. This can be efficiently implemented using the Hadoop Framework as it can process large datasets with less cost and good performance. We have proposed an efficient algorithm for MapReduce Apriori based on Hadoop- MapReduce model using Vertical Database Layout and Set Theory concept of Intersection.

Keywords

Apriori Hadoop MapReduce Cloud computing Association rule Frequent itemset mining 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Amrita School of Arts and Sciences Amrita Vishwa VidyapeethamKochiIndia

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