Abstract: This review article provides a thorough assessment of modern and innovative algorithms for text classification through both observational and experimental evaluations. We propose a new ...

Traditional machine learning algorithms for classification tasks operate under the assumption of balanced class distributions. However, this assumption only holds in some practical scenarios. In most ...

ABSTRACT: Text classification plays a critical role in numerous natural language processing applications, yet limited work has addressed the unique linguistic structure of African languages such as ...

Convert raw customer feedback into a strategic advantage that helps you stay ahead of competitors. Implement a structured process to turn unstructured survey comments into measurable, organized data ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

Background: Free-text comments in patient-reported outcome measures (PROMs) data provide insights into health-related quality of life (HRQoL). However, these comments are typically analysed using ...

The Toxic Comments Classifier is a robust machine learning tool implemented in C++ designed to identify toxic comments in digital conversations. Featuring a custom-built multi-layer perceptron (MLP) ...

ABSTRACT: This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional ...