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

Authors:
Ying Liu;Wei-keng Liao;Alok Choudhary
Affiliations:
Electrical and Computer Engineering Department, Northwestern University, Evanston, IL;Electrical and Computer Engineering Department, Northwestern University, Evanston, IL;Electrical and Computer Engineering Department, Northwestern University, Evanston, IL
Venue:
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Year:
2005

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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.