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 …

Mining patterns with high utilization (or called high-utility itemset mining, HUIM) is
considered a major issue in recent decades especially in the market (eg, supermarket) …

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) …

Fog computing (FC) is an emerging paradigm that extends computation, communication,
and storage facilities towards the edge of a network. In this heterogeneous and distributed …

Abstract High-Utility Itemset (HUI) mining is an important data-mining task which has gained
popularity in recent years due to its applications in numerous fields. HUI mining aims at …

Abstract High-Utility Itemset Mining (HUIM) is considered a major issue in recent decades
since it reveals profit strategies for use in industry for decision-making. Most existing works …

Processing changeable data streams in real time is one of the most important issues in the
data mining field due to its broad applications such as retail market analysis, wireless sensor …

Abstract The study of High-Utility Itemset Mining (HUIM) and Frequent Itemset Mining (FIM)
is crucial since it explains consumer behavior and offers actionable advice to improve …

Top-k high utility itemset mining is the process of discovering the k itemsets having the
highest utilities in a transactional database. In recent years, several algorithms have been …