The vast amounts of mobile communication data collected by mobile operators can provide
important insights regarding epidemic transmission or traffic patterns. By analyzing historical …

High-utility sequential pattern mining (HUSPM) is a hot research topic in recent decades
since it combines both sequential and utility properties to reveal more information and …

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 …

High utility pattern mining has been proposed to overcome the limitations of frequent pattern
mining which cannot reflect the unique profits of items. High utility pattern mining has been …

In recent decades, mobile or the Internet of Thing (IoT) devices are dramatically increasing
in many domains and applications. Thus, a massive amount of data is generated and …

In contrast to frequent itemset mining (FIM) algorithms that focus on identifying itemsets with
high occurrence frequency, high-utility itemset mining algorithms can reveal the most …

Many researchers have been investigating and applying a new trend of data mining, namely
high occupancy itemset mining. Frequent itemset mining often returns a large set of itemsets …

We propose a method to search rare cardiovascular disease symptom rules from historical
health examination records according to its hazard ratio utility and further detect the disease …

The discovery of frequent closed high utility itemsets (FCHUIs) and frequent generators of
high utility itemsets (FGHUIs) is significant because they serve as important and concise …

Analyzing customer transactions to discover high-utility itemsets is a popular task, which
consists of finding the sets of items that are purchased together and yield a high profit …