Fast algorithm for mining multilevel association rules

In this paper, we present two algorithms AprioriNewMulti and AprioriNewSingle, for Data Mining multilevel and single level association rules in large database respectively. The database consists of following fields, Transaction ID and items purchased in the transaction. The algorithms introduce a new concept called multi minimum support i.e. minimum support will vary for different lenght of the itemset. Unlike other algorithms AprioriNewMulti does not depend on number of levels in concept hierarchy i.e. it doesn't scan the database for each level of abstraction for finding assocation rules. Scale up experiments show that both of these algorithms have scale linear with the number of customer transaction.