A Study for Statistical Criterion in Negative Association Rules Using Boolean Analyzer

  • Shin, Sang-Jin (Department of Statistics, Changwon National University) ;
  • Lee, Keun-Woo (Department of Statistics, Changwon National University)
  • Published : 2006.11.17

Abstract

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule support and confidence and lift. Association rule is an interesting rule among purchased items in transaction, but the negative association rule is an interesting rule that includes items which are not purchased. Boolean Analyzer is the method to produce the negative association rule using PIM. But PIM is subjective. In this paper, we present statistical objective criterion in negative association rules using Boolean Analyzer.