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http://dx.doi.org/10.7465/jkdi.2012.23.4.717

Association rule thresholds considering the number of possible rules of interest items  

Park, Hee-Chang (Department of Statistics, Changwon National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.23, no.4, 2012 , pp. 717-725 More about this Journal
Abstract
Data mining is a method to find useful information for large amounts of data in database. One of the well-studied problems in data mining is exploration for association rules. Association rule mining searches for interesting relationships among items in a given database by support, confidence, and lift. If we use the existing association rules, we can commit some errors by information loss not to consider the size of occurrence frequency. In this paper, we proposed a new association rule thresholds considering the number of possible rules of interest items and compare with existing association rule thresholds by example and real data. As the results, the new association rule thresholds were more useful than existing thresholds.
Keywords
Association rule; confidence; lift; number of possible rules; support;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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