Itemset mining is an important subfield of data mining, which consists of discovering
interesting and useful patterns in transaction databases. The traditional task of frequent …

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 …

In recent years, high-utility itemset mining has emerged as an important data mining task.
However, it remains computationally expensive both in terms of runtime and memory …

Mining useful patterns from varied types of databases is an important research topic, which
has many reallife applications. Most studies have considered the frequency as sole …

Mining high utility itemsets is an emerging and very active research area in data mining. The
goal is to mine all itemsets with a utility value, in terms of importance to the user, no less than …

Among internet and smart device applications, Twitter has become a leading social media
platform, disseminating online events occurring in the world on a real-time basis. Many …

High-utility sequential pattern (HUSP) mining is an emerging topic in the field of knowledge
discovery in databases. It consists of discovering subsequences that have a high utility …

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 …

For sequence classification, an important issue is to find discriminative features, where
sequential pattern mining (SPM) is often used to find frequent patterns from sequences as …

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 …