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 …

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 …

High utility itemset mining is a challenging task in frequent pattern mining, which has wide
applications. The state-of-the-art algorithm is HUI-Miner. It adopts a vertical representation …

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 …

Mining high utility itemsets from a transactional database refers to the discovery of itemsets
with high utility like profits. Although a number of relevant algorithms have been proposed in …

It is widely known that there is a lot of useful information hidden in big data, leading to a new
saying that “data is money.” Thus, it is prevalent for individuals to mine crucial information for …

Mining high utility itemsets from a transactional database refers to the discovery of itemsets
with high utility like profits. Although a number of relevant approaches have been proposed …

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 …

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 problem involves the use of internal and external utilities of items
(such as profits, margins) to discover interesting patterns from a given transactional …