Traditional association rule mining has been widely studied. But it is unsuitable for real‐
world applications where factors such as unit profits of items and purchase quantities must …

Abstract The High Average Utility Itemset Mining (HAUIM) technique, a variation of High
Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most …

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 …

Data mining methods have been required in both commercial and non-commercial areas. In
such circumstances, pattern mining techniques can be used to find meaningful pattern …

High utility itemset mining problem uses the notion of utilities to discover interesting and
actionable patterns. Several data structures and heuristic methods have been proposed in …

High average utility pattern mining is the concept proposed to complement drawbacks of
high utility pattern mining by considering lengths of patterns along with the utilities of the …

Mining high average-utility itemsets (HAUIs) is a promising research topic in data mining
because, in contrast to high utility itemsets, they are not biased toward long itemsets …

Aiming at the performance bottleneck of traditional Apriori algorithm when the data set is
slightly large, this paper adopts the idea of parallelization and improves the Apriori algorithm …

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 …

High utility pattern mining has been actively researched as one of the significant topics in the
data mining field since this approach can solve the limitation of traditional pattern mining that …