An efficient projection-based indexing approach for mining high utility itemsets

Guo Cheng Lan, Tzung Pei Hong*, Vincent S. Tseng

*Corresponding author for this work

Research output: Contribution to journalArticle

87 Scopus citations

Abstract

Recently, utility mining has widely been discussed in the field of data mining. It finds high utility itemsets by considering both profits and quantities of items in transactional data sets. However, most of the existing approaches are based on the principle of levelwise processing, as in the traditional two-phase utility mining algorithm to find a high utility itemsets. In this paper, we propose an efficient utility mining approach that adopts an indexing mechanism to speed up the execution and reduce the memory requirement in the mining process. The indexing mechanism can imitate the traditional projection algorithms to achieve the aim of projecting sub-databases for mining. In addition, a pruning strategy is also applied to reduce the number of unpromising itemsets in mining. Finally, the experimental results on synthetic data sets and on a real data set show the superior performance of the proposed approach.

Original languageEnglish
Pages (from-to)85-107
Number of pages23
JournalKnowledge and Information Systems
Volume38
Issue number1
DOIs
StatePublished - 1 Jan 2014

Keywords

  • Data mining
  • High transaction-weighted utilization itemsets
  • High utility itemsets
  • Indexing mechanism
  • Utility mining

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