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Natural Language Processing: An Overview of Models, Transformers and Applied Practices

Santiago Canchila¹  , Carlos Meneses-Eraso²  , Javier Casanoves-Boix³  , Pascual Cortés-Pellicer⁴   and Fernando Castelló-Sirvent⁵  

1. Universidad Sergio Arboleda
   Calle 74 No. 14 - 14 Bogotá, Colombia
   santiago.canchila01@usa.edu.co
2. Universidad Sergio Arboleda
   Calle 74 No. 14 - 14 Bogotá, Colombia
   carlos.meneses@usa.edu.co
3. Universidad Alfonso X El Sabio
   Avda. de la Universidad, 1. Villanueva de la Cañada, 28691, Madrid, Spain
   jcasaboi@uax.es
4. Department of Business Management Universitat Politècnica de València (UPV)
   Camí de Vera, s/n - 46022 València, Spain
   pascorpe@omp.upv.es
5. Department of Business Management Universitat Politècnica de València (UPV)
   Camí de Vera, s/n - 46022 València, Spain
   fernando.castello@upv.es

Abstract

The study of utilizing human language in computer systems referred to as NLP, is becoming increasingly significant in various aspects of life, including research, daily activities, commerce, and entrepreneurship endeavors. A multitude of tech companies are dedicating resources towards the development and improvement of NLP methods, models, and products. To add to that, open-source contributions to the field are on the rise. However, with so much progress being made, it may be challenging to understand the current state of NLP and what models are considered to be the most efficient. To help those grappling with the fast-paced and constantly evolving NLP landscape, we have put together a comprehensive overview of the latest NLP research and advancements.

Key words

NLP, Deep Learning, Transformers

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS230217031C

Publication information

Volume 21, Issue 3 (June 2024)
Year of Publication: 2024
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

Available in PDF
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How to cite

Canchila, S., Meneses-Eraso, C., Casanoves-Boix, J., Cortés-Pellicer, P., Castelló-Sirvent, F.: Natural Language Processing: An Overview of Models, Transformers and Applied Practices. Computer Science and Information Systems, Vol. 21, No. 3, 1097-1145. (2024), https://doi.org/10.2298/CSIS230217031C