Bias in textual data can lead to skewed interpretations and outcomes when the data is used.
These biases could perpetuate stereotypes, discrimination, or other forms of unfair …

The control of the froth flotation process in the mineral industry is a challenging task due to
its multiple impacting parameters. Accurate and convenient examination of the concentrate …

Feature selection is an indispensable aspect of modern machine learning, especially for
high-dimensional datasets where overfitting and computational inefficiencies are common …

Intention recognition of non-cooperative target is an important basis for battlefield command
decision-making. Recent advances suggest recognizing target intention from a perspective …

In the realm of cybersecurity, the detection and analysis of obfuscated malware remain a
critical challenge, especially in the context of memory dumps. This research paper presents …

In emergency call centers, operators are required to analyze and prioritize emergency
situations prior to any intervention. This allows the team to deploy resources efficiently if …

Dynamic constrained multi-objective optimization problems (DCMOPs) involve objectives,
constraints, and parameters that change over time. This kind of problem presents a greater …

Partial multi-label learning (PML) addresses problems where each instance is assigned a
candidate label set and only a subset of these candidate labels is correct. The major …

Existing data mining-based meta-heuristic approaches have endeavored to efficiently solve
the Quadratic Assignment Problem (QAP). However, their captured heuristic information …

Frequent itemset mining (FIM) is a widely used task that extracts frequently occurring
itemsets from data. Plenty of deterministic algorithms are available for this daunting task …