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Association Rule Mining and Refinement Using Shared Memory Multiprocessor Environment

  • P. Asha
  • T. Jebarajan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 325)

Abstract

Rules that represent an association between the values of certain attributes and those of others are called association rules. The process of extracting such rules from a given dataset is called association rule mining (ARM). The work aims at effective utilization of all the cores present in the system with less time wastage and also balance the workload among them. Full fledged use of system resources and load balance can be achieved by perfect scheduling and providing efficient parallel algorithms. This paper discusses such a parallel ARM algorithm and rule generation based on the frequent combinations obtained. As the rules generated are also more in number as well as redundant, insignificant, and unproductive, it is compulsory to filter and refine the rules.

Keywords

Data mining Candidate generation Rule filtration Interestingness measures Parallelism 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentSathyabama UniversityChennaiIndia
  2. 2.Computer Science and EngineeringRajalakshmi Engineering CollegeChennaiIndia

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