his paper considers a frequent itemsets mining in transactional databases. It introduces a new technique Dynamic Cardinality Count (DCC) to reduce the candidate itemset generation in each intermediate pass for finding the frequent itemsets. The proposed approach uses the statistical technique of cardinality count for candidate set generation. The algorithm is dynamic in nature where after each pass it eliminates the infrequent itemsets. The number of candidate sets generated before and after pruning steps in our proposed method is less as compare to the Apriori Algorithm that leads to save the computational and the storage cost.
Volume 11 | 08-Special Issue
Pages: 3048-3052