The rapid progress in deep learning has propelled transformer-based models to the
forefront, establishing them as leading solutions for a multiple NLP tasks. These tasks span …

The growth in textual data associated with the increased usage of online services and the
simplicity of having access to these data has resulted in a rise in the number of text …

Spelling errors in textual content may significantly hinder communication and
comprehension, particularly in formal writing, such as news or reports. Thus, it becomes …

Text categorization (TC) is one of the most useful automatic tools in today's world to organize
huge text data automatically. It is widely used by practitioners to classify texts automatically …

As a well-known Natural Language Processing (NLP) task, text classification can be defined
as the process of categorizing documents depending on their content. In this process …

Text classification is a common way of working in computer applications, in daily work, the
accurate and efficient classification of diverse categories of texts is a work problem that …

The capabilities of deep models are constantly mined for extraction and representation of
features among text classification tasks. However, these models are sensitive to changes in …

Text categorization (TC) is a natural language processing (NLP) task commonly used in text
mining. It is defined as the automatic assignment of text to a set of given categories …

Language use on online platforms has dramatically expanded over the last ten years.
Turkish text natural language processing (NLP) research, however, has not gotten much …

In this study, preprocessings with all combinations were examined in terms of the effects on
decreasing word number, shortening the duration of the process and the classification …