An Enhanced FUFP-Tree Maintenance Approach for Transaction Deletion

The fast updated frequent pattern tree (FUFP-tree) is an efficient data structure for association-rule mining. Hong et al. (2009) proposed an approach for the maintenance of the FUFP-tree structure after the deletion of transactions. However, all transactions in the original database might need to be rescanned to determine the occurrence of infrequent items, which were not stored during the mining and maintenance process. The rescanning process steps can be time-consuming depending on the original database size and number of rescanned items. The study in this paper enhances Hong et. al.'s approach. In the proposed algorithm, the infrequent 1-itemsets are stored during the maintenance process and the rescanned items are pruned out step by step to reduce execution time. Experimental results verify the performance of the proposed algorithm.