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 (HUIs) mining is an emerging topic in data mining, which refers to
discovering all itemsets having a utility meeting a user-specified minimum utility threshold …

High-utility itemset mining is a popular data mining problem that considers utility factors,
such as quantity and unit profit of items besides frequency measure from the transactional …

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 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 …

Association rule mining is a technique that is widely used in data mining. This technique is
used to identify interesting relationships between sets of items in a dataset and predict …

High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to
reveal the profitable products by considering both the quantity and profit factors instead of …

Discovering high utility itemsets in transaction databases is a key task for studying the
behavior of customers. It consists of finding groups of items bought together that yield a high …

Association-rule mining (ARM) or frequent itemset mining (FIM) is the most fundamental task
in knowledge discovery, which is used to find the occurrence frequency of the item/sets in …