Efficiently Finding High Utility-Frequent Itemsets Using Cutoff and Suffix Utility

  • R. Uday KiranEmail author
  • T. Yashwanth Reddy
  • Philippe Fournier-Viger
  • Masashi Toyoda
  • P. Krishna Reddy
  • Masaru Kitsuregawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11440)


High utility itemset mining is an important model with many real-world applications. But the popular adoption and successful industrial application of this model has been hindered by the following two limitations: (i) computational expensiveness of the model and (ii) infrequent itemsets may be output as high utility itemsets. This paper makes an effort to address these two limitations. A generic high utility-frequent itemset model is introduced to find all itemsets in the data that satisfy user-specified minimum support and minimum utility constraints. Two new pruning measures, named cutoff utility and suffix utility, are introduced to reduce the computational cost of finding the desired itemsets. A single phase fast algorithm, called High Utility Frequent Itemset Miner (HU-FIMi), is introduced to discover the itemsets efficiently. Experimental results demonstrate that the proposed algorithm is efficient.


Data mining Itemset mining Utility itemset 



We would like to thank Yahoo Japan Corporation for providing the retail transaction data.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • R. Uday Kiran
    • 1
    • 2
    Email author
  • T. Yashwanth Reddy
    • 3
  • Philippe Fournier-Viger
    • 4
  • Masashi Toyoda
    • 2
  • P. Krishna Reddy
    • 3
  • Masaru Kitsuregawa
    • 2
    • 5
  1. 1.National Institute of Information and Communications TechnologyTokyoJapan
  2. 2.The University of TokyoTokyoJapan
  3. 3.International Institute of Information Technology-HyderabadHyderabadIndia
  4. 4.Harbin Institute of Technology (Shenzhen)ShenzhenChina
  5. 5.National Institute of InformaticsTokyoJapan

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