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 itemset mining (HUIM) is an important data mining task with wide applications. In
this paper, we propose a novel algorithm named EFIM (EFficient high-utility Itemset Mining) …

HUIM (High utility itemset mining) is a key problem in data mining. The goal is to find
itemsets having a high importance or profit in a database, to identify useful knowledge that …

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 …

High utility itemset mining is an emerging data mining task, which consists of discovering
highly profitable itemsets (called high utility itemsets) in very large transactional databases …

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 …

High-utility itemset mining (HUIM) is a popular data mining task with applications in
numerous domains. However, traditional HUIM algorithms often produce a very large set of …

Discovering high average utility itemsets (HAUIs) in a quantitative database is a popular
data mining task, which aims at identifying sets of products (items) purchased together that …

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 itemset mining problem uses the notion of utilities to discover interesting and
actionable patterns. Several data structures and heuristic methods have been proposed in …