An Intelligent Decision in Smart Systems Using A Weighted Frequent Itemset Mining Algorithm

Authors

  • K. Lavanya  Computer Science and Engineering,VasireddyVenkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • K. Triveni  Computer Science and Engineering,VasireddyVenkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • K. Bala Mamatha3  Computer Science and Engineering,VasireddyVenkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • K. Meghana  Computer Science and Engineering,VasireddyVenkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • Dr. G. Sanjay Gandhi  Professor of CSE, VasireddyVenkatadri Institute of Technology, Guntur, Andhra Pradesh, India

DOI:

https://doi.org//10.32628/CSEIT1195296

Keywords:

Frequent itemset mining, Weight judgment, Downward closure property,Intelligent decision, Smart system, Association Rule Mining (ARM),Data mining.

Abstract

Intelligent decision is the key technology of smart systems. Data mining technology has been playing an increasingly important role in decision making activities. The introduction of weight makes the weighted frequent itemsets not satisfy the downward closure property any longer. As a result, the search space of frequent itemsets cannot be narrowed according to downward closure property which leads to a poor time efficiency. In this paper, the weight judgment downward closure property for weighted frequent itemsets and the existence property of weighted frequent subsets are introduced and proved first. The Fuzzy-based WARM satisfies the downward closure property and prunes the insignificant rules by assigning the weight to the itemset. This reduces the computation time and execution time. This paper presents an Enhanced Fuzzy-based Weighted AssociationRuleMining(E-FWARM) algorithm for efficient mining of the frequent itemsets. The pre-filtering method is applied to the input dataset to remove the item having low variance. Data discretization is performed and E-FWARM is applied for mining the frequent itemsets. The experimental results show that the proposed E-FWARM algorithm yields maximum frequent items, association rules, accuracy and minimum execution time than the existing algorithms.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

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How to Cite

[1]
K. Lavanya, K. Triveni, K. Bala Mamatha3, K. Meghana, Dr. G. Sanjay Gandhi, " An Intelligent Decision in Smart Systems Using A Weighted Frequent Itemset Mining Algorithm, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.1109-1119, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1195296