The main purpose of data mining and analytics is to find novel, potentially useful patterns
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …

High utility itemsets refer to the sets of items with high utility like profit in a database, and
efficient mining of high utility itemsets plays a crucial role in many real-life applications and …

Recently, high utility pattern (HUP) mining is one of the most important research issues in
data mining due to its ability to consider the nonbinary frequency values of items in …

Recently, utility mining has widely been discussed in the field of data mining. It finds high
utility itemsets by considering both profits and quantities of items in transactional data sets …

RFM analysis and market basket analysis (ie, frequent pattern mining) are two most
important tasks in database marketing. Based on customers' historical purchasing behavior …

It is conventional wisdom in machine learning and data mining that logical models such as
rule sets are more interpretable than other models, and that among such rule-based models …

This study proposes a novel framework for designing business rule analytics to assist
businesses offering digital content in effectively converting free-only users (FOUs) into …

Recently, a utility-based mining approach has emerged as an alternative mechanism to
frequency-based mining in an attempt to reflect not only the statistical correlation but also the …

Utility mining has recently been an emerging topic in the field of data mining. It finds out high
utility itemsets by considering both the profits and quantities of items in transactions. It may …

Mining high utility itemsets are the basic task in the area of frequent itemset mining (FIM) that
has various applications in diverse domains, including market basket analysis, web mining …