An efficient algorithm for high utility sequential pattern mining

Jun Zhe Wang, Zong Hua Yang, Jiun-Long Huang*

*Corresponding author for this work

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

4 Scopus citations

Abstract

High utility sequential pattern mining is to mine sequences with high utility (e.g. profits) but probably with low frequency. In some applications such as marketing analysis, high utility sequential patterns are usually more useful than sequential patterns with high frequency. In this paper, we devise two pruning strategies RSU and PDU, and propose HUS-Span algorithm based on these two pruning strategies to efficiently identify high utility sequential patterns. Experimental results show that HUS-Span algorithm outperforms prior algorithms by pruning more low utility sequences.

Original languageEnglish
Title of host publicationFrontier and Innovation in Future Computing and Communications
EditorsAlbert Zomaya, James J. Park, Hwa-Young Jeong, Mohammad Obaidat
PublisherSpringer Verlag
Pages49-56
Number of pages8
ISBN (Electronic)9789401787970
DOIs
StatePublished - 1 Jan 2014
Event2014 FTRA International Symposium on Frontier and Innovation in Future Computing and Communications, FCC 2014 - Auckland, New Zealand
Duration: 13 Jan 201416 Jan 2014

Publication series

NameLecture Notes in Electrical Engineering
Volume301
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference2014 FTRA International Symposium on Frontier and Innovation in Future Computing and Communications, FCC 2014
CountryNew Zealand
CityAuckland
Period13/01/1416/01/14

Keywords

  • High utility sequences
  • High utility sequential pattern mining
  • Utility mining

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