A space-time trade off for FUFP-trees maintenance

Abstract

In the past, Hong et al. proposed an algorithm to maintain the fast updated frequent pattern tree (FUFP-tree), which was an efficient data structure for association-rule mining. However in the maintenance process, the counts of infrequent items and the IDs of transactions with those items were determined by rescanning all the transactions in the original database. This step might be quite time-consuming depending on the number of transactions in the original database and the number of rescanned items. This study improves that approach by storing 1-items during the maintenance process and based on the properties of FUFP-trees, such that the rescanned items and inserted items are processed more efficiently to reduce execution time. Experimental results show that the improved algorithm needs some more memory to store infrequent 1-items but the performance is better than the original one. © 2013 Springer-Verlag.