A two-phase algorithm for fast discovery of high utility itemsets

Ying Liu*, Wei Keng Liao, Alok Choudhary

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

387 Scopus citations

Abstract

Traditional association rules mining cannot meet the demands arising from some real applications. By considering the different values of individual items as utilities, utility mining focuses on identifying the itemsets with high utilities. In this paper, we present a Two-Phase algorithm to efficiently prune down the number of candidates and precisely obtain the complete set of high utility itemsets. It performs very efficiently in terms of speed and memory cost both on synthetic and real databases, even on large databases that are difficult for existing algorithms to handle.

Original languageEnglish (US)
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings
PublisherSpringer Verlag
Pages689-695
Number of pages7
ISBN (Print)3540260765, 9783540260769
DOIs
StatePublished - Jan 1 2005
Event9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005 - Hanoi, Viet Nam
Duration: May 18 2005May 20 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3518 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005
CountryViet Nam
CityHanoi
Period5/18/055/20/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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