期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2012
卷号：4
期号：4
页码：97
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Association rules is one of data mining methods for discovering knowledge from large amounts of data indatabases. In this paper, we propose an intelligent method for discovering association rules, called IMAR.IMAR is designed through three main phases, i.e., preprocessing, processing and post processing. It hasbeen experimented using three domain data sets, i.e., Australian Credit Card (ACC), Jakarta StockExchange (JSX), and Cleveland Heart Diseases (CLEV) data sets. Our experimental results show thatIMAR can (i) discover association rules from large inconsistent databases intelligently and accurately, and(ii) reduce the number of generated interesting association rules without losing information and withhigher accuracy.
关键词：Database; Data Mining; Association Rules; Knowledge; Information
