Efficient Algorithms for Mining Top-K High Utility Item sets

Abstract

High utility itemsets (HUIs) mining is a developing point in data mining, which alludes to finding all itemsets having an utility gathering a user-indicated least utility limit min_util. Nonetheless, setting min_util fittingly is a troublesome issue for users. As a rule, finding a suitable least utility limit by experimentation is a repetitive procedure for users. On the off chance that min_util is set too low, an excessive number of HUIs will be created, which may cause the mining procedure to be extremely inefficient. Then again, if min_util is set too high, it is likely that no HUIs will be found. In this paper, we address the above issues by proposing another system for best k high utility itemset mining, where k is the coveted number of HUIs to be mined.