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 …

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 considers the importance of items such as profit and item
quantities in transactions. Recently, mining high utility itemsets has emerged as one of the …

In pattern mining, users generally set a minimum threshold to find useful patterns from
databases. As a result, patterns with higher values than the user-given threshold are …

Nonoverlapping sequential pattern mining, as a kind of repetitive sequential pattern mining
with gap constraints, can find more valuable patterns. Traditional algorithms focused on …

Frequent pattern mining has become very useful and interesting to researchers due to its
high applicability. Different real-life databases (eg, sensor network, medical diagnosis data) …

The traditional methods for mining association rules (ARs) include two phrases: mining
frequent itemsets (FIs)/frequent closed itemsets (FCIs)/frequent maximal itemsets (FMIs) and …

Outstanding frequent pattern mining guarantees both fast runtime and low memory usage
with respect to various data with different types and sizes. However, it is hard to improve the …

A novel algorithm for efficiently mining high average-utility itemsets is presented in this
paper. The algorithm utilizes list structures, which compactly capture all information needed …

One of various pattern mining techniques, the High Utility Pattern Mining (HUPM) is a
method for finding meaningful patterns from non-binary databases by considering the …