Mining Influential Association Rules

X. Zhang, Z. Chen, Q. Zhu

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

Abstract

Recently integration of OLAP and data mining has drawn much attention, but there is still a lack of concrete result. In this paper we explore one aspect of such integration, called influential association rule mining. We first introduce the basic idea of association rule mining, and the two approaches, called IARM (Influential Association Rule Mining) and its improvement, IARMBM (Influential Association Rule Mining with BitMap) are briefly described. In addition, related experiments and comparisons are also reported.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
EditorsJ.H. Caulfield, S.H. Chen, H.D. Cheng, R. Duro, J.H. Caufield, S.H. Chen, H.D. Cheng, R. Duro, V. Honavar
Pages490-493
Number of pages4
StatePublished - 2002
EventProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 - Research Triange Park, NC, United States
Duration: Mar 8 2002Mar 13 2002

Publication series

NameProceedings of the Joint Conference on Information Sciences
Volume6

Conference

ConferenceProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
CountryUnited States
CityResearch Triange Park, NC
Period3/8/023/13/02

ASJC Scopus subject areas

  • Computer Science(all)

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