HLHUI: An improved version of local high utility itemset mining
Mohammad Sedghi, Mohammad Karim Sohrabi · Procedia Computer Science · 2023
High utility itemsets (HUIs) have been emerged to address the main problems of frequent itemset mining, namely considering the same importance for all items of the dataset and ignoring the occurrence numbers of items within transactions during the mining process. Local and peak HUIs were defined to mine the itemsets which are useful and high utility during specific periods of time. In this paper, using some adopted definitions and strategies of HMiner [19], an improved version of LHUI method [33], called HLHUI (Hminer-based Local HUI mining), is introduced that mines local HUIs using a utility-list-based approach. Performance evaluations of the proposed method show that it can efficiently find useful itemsets.