Study and analysis of incremental apriori algorithm

Abstract

Abstract. Study of this paper is based on finding the threshold value of database change up to which incremental Apriori algorithm performs better. A new incremental Apriori algorithm is also proposed which performs better than the existing algorithm in terms of computation time. The performance of frequent sets generation algorithms for dynamic databases is major problem, since numbers of runs are required to accommodate the database changes. It determines the value of change percentage of original database that decides whether the user can go for re-run the actual algorithm or use the previously computed result and generate the frequent sets in incremental fashion. The purpose of this paper is two folds. First is to avoid the scans of the older database, its corresponding support count effort for newly added records by using intermediate data and results. And second is to solve the efficient updating problem of association rules after a nontrivial number of new records have been added to a database. © 2011 Springer-Verlag.