High utility pattern mining is an emerging data science task, which consists of discovering
patterns having a high importance in databases. The utility of a pattern can be measured in …

Abstract High-Utility Itemset (HUI) mining is an important data-mining task which has gained
popularity in recent years due to its applications in numerous fields. HUI mining aims at …

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 …

Abstract The study of High-Utility Itemset Mining (HUIM) and Frequent Itemset Mining (FIM)
is crucial since it explains consumer behavior and offers actionable advice to improve …

Regular pattern mining has been emerged as one of the promising sub-domains of data
mining by discovering patterns with regular occurrences throughout a complete database. In …

Mining closed high utility itemsets (CHUIs) involves finding a representative set of HUIs that
is usually smaller than that of HUIs but can generate the full HUIs without loss of information …

Data mining has been actively studied, and it has become more important due to the
development of information technology and the demands of diverse applications, such as …

In practical applications, top-k high utility itemset mining (top-k HUIM) is an interesting
operation to find the k itemsets with the highest utilities. It is analyzed that, the existing …

A major limitation of traditional High Utility Itemset Mining (HUIM) algorithms is that they do
not consider that the utility of itemsets may vary over time. Thus, traditional HUIM algorithms …

Closed high utility itemsets (CHUIs) and maximal high utility itemsets (MaxHUIs) are two
important concise representations of HUIs. Discovering these itemsets is important because …