Mining high utility itemsets from massive data is one of the most active research directions in
data mining at present. Intelligent optimization algorithms have been applied to the high …

In this paper, high utility itemset mining (HUIM) algorithms driven by Binary Differential
Evolution (BDE) and an Adaptive Binary Differential Evolution (ABDE) are proposed …

High utility pattern mining has been proposed to overcome the limitations of frequent pattern
mining which cannot reflect the unique profits of items. High utility pattern mining has been …

Top-k high utility itemsets (HUIs) mining permits discovering the required number of patterns-
k, without having an optimal minimum utility threshold (ie, minimum profit). Multiple top-k …

Mining high-utility itemsets (HUIs) is one of the most important research topics in data mining
because HUIs consider non-binary frequency values of items in transactions and different …

High-utility item-set mining has become a very crucial topic of research in recent times. It is
used to find profitable products utilizing both profit factors and the quantity as opposed to the …

Mining a closed high-utility itemset is a prevalent research task in analyzing transaction
databases. However, numerous target itemsets are generated in the closed high-utility …

Extraction of interesting patterns from large databases have placed great impact on many
applications for instance market basket analysis, web service mining, bio-informatics and …

Mining high utility itemsets (HUIs) from transaction databases is one of the current research
areas in the data mining field. HUI mining finds itemsets whose utility meets a predefined …

Metaheuristics are dilemma-independent methods that are generalizedin a variety of
problems. In the real world, various problems are solved using generalized dilemma …