Mining high utility itemsets from massive data is one of the most active research directions in
data mining at present. Intelligent optimization algorithms have been applied to the high …

Mining high utility itemsets is an emerging and very active research area in data mining. The
goal is to mine all itemsets with a utility value, in terms of importance to the user, no less than …

HUIM (High utility itemset mining) is a key problem in data mining. The goal is to find
itemsets having a high importance or profit in a database, to identify useful knowledge that …

As an essential data mining task, high-utility itemset mining (HUIM) has attracted a lot of
research. With the increase of dataset size, traditional exact HUIM algorithms are faced with …

Heuristic algorithms have been developed to find approximate solutions for high-utility
itemset mining (HUIM) problems that compensate for the performance bottlenecks of exact …

Mining high-utility itemsets (HUIs) is one of the most important research topics in data mining
because HUIs consider non-binary frequency values of items in transactions and different …

The discovery of high utility itemsets (HUIs) is an attractive topic in data mining. Because of
its high computational cost, using heuristic methods is a promising approach to rapidly …

Mining high utility itemsets (HUIs) from transaction databases is one of the current research
areas in the data mining field. HUI mining finds itemsets whose utility meets a predefined …

High-utility item-set mining has become a very crucial topic of research in recent times. It is
used to find profitable products utilizing both profit factors and the quantity as opposed to the …

High-utility itemsets mining (HUIM) is an important research topic in data mining that
consists of extracting efficient itemsets that generate high profit in databases. Metaheuristic …