A novel algorithm for mining fuzzy high utility itemsets

Cheng Ping Lai*, Pau Choo Chung, S. Tseng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Utility mining is to find the itemsets in a transaction database with high utility values like profits. Although a number of algorithms on high utility mining have been proposed, they did not reflect the fuzzy degree of quantity and profit level for mined high utility itemsets, which are essential for decision making in various applications like stock control and sales analysis. In this paper, we explore to apply fuzzy sets theory to the utility mining problem and propose a novel method, namely FHUI (Fuzzy High Utility Itemsets)-Mine, for mining fuzzy high utility itemsets. In addition to reflecting the fuzzy degree for quantity and profit regions of high utility itemsets, FHUI-Mine also provides a fuzzy threshold range that may include itemsets with profits slightly less than the designated threshold value. To prove the feasibility of FHUI-Mine, it was compared with the well-known Two-Phase algorithm through experimental evaluation. The results show that FHUI-Mine delivers higher mining capability since it can not only mine all high utility itemsets found by Two-Phase algorithm but also discover additional itemsets that are potentially high utility ones.

Original languageEnglish
Pages (from-to)4347-4361
Number of pages15
JournalInternational Journal of Innovative Computing, Information and Control
Volume6
Issue number10
StatePublished - 1 Oct 2010

Keywords

  • Fuzzy data mining
  • Fuzzy sets theory
  • High utility itemset
  • Utility mining

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