Efficient search for association rules

This paper argues that for some applications direct search for association rules can be more e cient than the tw o stage process of the Apriori algorithm which rst nds large itemsets whic hare then used to iden tify associations. In particular, it is argued, Apriori can impose large computational overheads when the number of frequen titemsets is very large. This will often be the case when association rule analysis is performed on domains other than basket analysis or when it is performed for basket analysis with basket information augmented b y other customer information. An algorithm is presented that is computationally e cient for association rule analyses during which the n um ber of rules to be found can be constrained and all data can be maintained in memory.