The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …

It is indispensable to understand where the development of the Environmental-Social-
Governance (further-ESG) concept is moving. People need to know where to develop in the …

The rapid increase in obtainable online text data has made text categorization an important
tool for data analysts to extract relevant information on the web. However, incorrect or …

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 …

Effective learning schemes such as fine-tuning, zero-shot, and few-shot learning, have been
widely used to obtain considerable performance with only a handful of annotated training …

The study focuses on news category prediction and investigates the performance of
sentence embedding of four transformer models (BERT, RoBERTa, MPNet, and T5) and …

Preprocessing is a crucial step for each task related to text classification. Preprocessing can
have a significant impact on classification performance, but at present there are few large …

Road safety analysis is typically performed by domain experts on the basis of the information
contained in accident reports. The main challenges are the difficulty of considering a large …

With the recent growth of the Internet, the volume of data has also increased. In particular,
the increase in the amount of unstructured data makes it difficult to manage data …

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 …