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Rare Correlated High Utility Itemsets Mining: An Experimental Approach

  • P. Lalitha Kumari
  • S. G. Sanjeevi
  • T. V. Madhusudhana Rao
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

High utility itemsets are having utility more than user-specified minimum utility. These itemsets provide high profit but do not exhibit correlation between them. High utility itemsets mining generate huge number of itemsets considering only single interesting criteria. Existing algorithm mines correlated high utility itemsets mining extracts itemsets that provide high utility with correlation between them. The limitation of this algorithm is that it does not consider the rarity of itemsets. To overcome this limitation, this proposed algorithm mines rare correlated high utility itemsets. Firstly, it mines correlated high utility itemsets. Secondly, it determines whether the itemsets support is no greater than minsup specified by the user. It can be shown by experimental results that the proposed algorithm reduces considerably runtime and number of candidate itemsets.

Keywords

Correlated itemsets Rare itemsets Correlated high utility itemsets Frequent itemsets 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • P. Lalitha Kumari
    • 1
  • S. G. Sanjeevi
    • 1
  • T. V. Madhusudhana Rao
    • 2
  1. 1.Department of CSENational Institute of TechnologyWarangalIndia
  2. 2.Department of CSESri Sivani College of EngineeringSrikakulamIndia

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