Updating high average-utility itemsets in dynamic databases

Guo Cheng Lan*, Chun Wei Lin, Tzung Pei Hong, Vincent Shin-Mu Tseng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In this paper, a maintenance algorithm for average-utility mining is proposed to update derived high average-utility itemsets in dynamic databases. It first calculates the count difference of modified itemsets and then partitions them into four parts according to whether they are high upper-bound average-utility itemsets in the original database and whether their count difference is positive or negative. Each part is then processed in its own way. Experimental results show the proposed maintenance algorithm runs faster than the two-phase approach for mining high average-utility itemsets in dynamic databases.

Original languageEnglish
Title of host publicationWCICA 2011 - 2011 World Congress on Intelligent Control and Automation, Conference Digest
Pages932-936
Number of pages5
DOIs
StatePublished - 9 Sep 2011
Event2011 World Congress on Intelligent Control and Automation, WCICA 2011 - Taipei, Taiwan
Duration: 21 Jun 201125 Jun 2011

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference2011 World Congress on Intelligent Control and Automation, WCICA 2011
CountryTaiwan
CityTaipei
Period21/06/1125/06/11

Keywords

  • Utility mining
  • average utility
  • dynamic database
  • maintenance algorithm
  • two-phase approach

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