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High Utility Infrequent Itemset Mining Using a Customized Ant Colony Algorithm

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Abstract

Itemset mining is a popular extension to the frequent pattern mining problem in data mining. Finding infrequent patterns, however, has gained its importance due to proven utility in the areas of web mining, bioinformatics and others. High utility mining refines the problem focus to identifying business-relevant transaction patterns that take purchase quantities and monetary considerations into account, like unit price and cost, typically to identify patterns of profit potential. High utility infrequent itemset mining unveils rare cases of highly profitable itemsets. This paper proposes a customized Ant colony algorithm for the efficient discovery of high utility infrequent itemsets. The mining performance of proposed algorithm is analyzed on four real time datasets namely chess, food mart, mushroom and retail.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Erode, Tamilnadu, 638401, India

    M. S. Arunkumar

  2. Department of Information Technology, Kongu Engineering College, Erode, Tamilnadu, 638052, India

    P. Suresh

  3. School of Information Technology and Engineering, VIT University, Vellore, Tamilnadu, 632014, India

    C. Gunavathi

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  1. M. S. Arunkumar
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  2. P. Suresh
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  3. C. Gunavathi
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Correspondence to M. S. Arunkumar.

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Arunkumar, M.S., Suresh, P. & Gunavathi, C. High Utility Infrequent Itemset Mining Using a Customized Ant Colony Algorithm. Int J Parallel Prog 48, 833–849 (2020). https://doi.org/10.1007/s10766-018-0621-7

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  • DOI: https://doi.org/10.1007/s10766-018-0621-7

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