A fast maintenance algorithm of the discovered high-utility itemsets with transaction deletion

Abstract

High-utility itemset mining (HUIM) has been recently studied to mine high-utility itemsets (HUIs) from the transac- tional database by considering more factors such as profit and quantity. Many approaches have been proposed for HUIM from a static database. Fewer studies have been developed to maintain the discovered HUIs in dynamic environment whether transac- tion insertion or transaction deletion. In the past, the FUP-HUI-DEL and PRE-HUI-DELalgorithms were respectively proposed to effectively maintain the discovered high transaction-weighted utilization itemsets (HTWUIs)and high-utility itemsets (HUIs) when the transactions are consequentially deleted from the original database. The original database is still, however, required to be rescanned when small transaction-weighted utilization itemsets in the original database are necessary to be maintained. In this paper, an efficient algorithm namely HUI-list-DEL is presented to discover HUIs by maintaining the built utility-list struc- ture for transaction deletion in dynamic databases. Based on the designed algorithm, the HUIs can be directly produced without candidate generation or the numerous database scans. Two pruning strategies are also designed to speed up the maintenance approach of HUIs. Substantial experiments show that the proposed maintenance approach for transaction deletion significantly outperforms the previous approaches in terms of execution time, memory consumption and scalability.