ABSTRACT

Now a days, Association rule plays an important role. The purchasing of one product when another product is purchased represents an association rule. The Apriori algorithm is the basic algorithm for mining massociation rules. This paper presents an efficient Partition Algorithm for Mining Frequent Itemsets(PAFI) using clustering. This algorithm finds the frequent itemsets by partitioning the database transactions into clusters. Clusters are formed based on the similarity measures between the transactions. Then it finds the frequent itemsets with the transactions in the clusters directly using improved Apriori algorithm which further reduces the number of scans in the database and hence improve the efficiency.