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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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A single-phase algorithm for mining high utility itemsets using compressed tree structures

  • Bhat B, Anup (Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education) ;
  • SV, Harish (Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education) ;
  • M, Geetha (Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education)
  • Received : 2020.08.05
  • Accepted : 2021.01.22
  • Published : 2021.12.01
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Abstract

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+algorithms.

Keywords

Acknowledgement

This work was supported by Manipal Academy of Higher Education Dr. T.M.A Pai Research Scholarship under Research Registration No. 170900117.

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