Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …

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 …

High utility itemset mining (HUIM) is the task of finding all items set, purchased together, that
generate a high profit in a transaction database. In the past, several algorithms have been …

As an important part of data mining, educational data mining (EDM) has played a significant
role in the field of education. This article reviews the development process of EDM …

Building prediction models with the right balance between performance and interpretability
is currently a great challenge in machine learning. A large number of recent studies have …

Contrast set mining is one of the most important tasks in the supervised descriptive pattern
mining field. It aims at finding patterns whose frequencies differ significantly among sets of …

Fuzzy utility (FU) pattern mining with an advantage in human reasoning has become one of
the interesting topics in studies of knowledge discovery. The discovered information in FU …

Genetic programming (GP) has been successfully applied to classification. However, GP
may evolve biased classifiers when encountering the problem of class imbalance. These …

Resource constraint job scheduling is an important combinatorial optimization problem with
many practical applications. This problem aims at determining a schedule for executing jobs …

During general anesthesia, anesthesiologists who provide anesthetic dosage traditionally
play a fundamental role to regulate bispectral index (BIS). However, in this article, an …