MINING ASSOCIATION RULES FOR LARGE TRANSACTIONS USING NEW SUPPORT AND CONFIDENCE MEASURES

Abstract

Association rule mining is to find out association rules that satisfy the predefined minimum support and confidence from a given database. End users of association rule mining tools encounter several in practice when data bases come with binary attributes. In this paper, we introduce a new measure, which does not require initially allotted weights .The quality of transactions is considered by link based models and a fast mining algorithm is adopted.