A comprehensive review of automatic text summarization techniques

Authors

  • Daniel O. Cajueiro Department of Economics, Universidade de Brasília (UnB), Brazil & Nacional Institute of Science and Technology for Complex Systems (INCT-SC), Universidade de Brasília (UnB), Brazil & Machine Learning Laboratory in Finance and Organizations (LAMFO), Universidade de Brasília (UnB), Brasília, Brazil
  • Arthur G. Nery Department of Economics, Universidade de Brasília (UnB), Brazil & Machine Learning Laboratory in Finance and Organizations (LAMFO), Universidade de Brasília (UnB), Brasília, Brazil
  • Igor Tavares Mechanic Engineering Department, Universidade de Brasília (UnB), Brazil
  • Maísa K. De Melo Department of Mathematics, Instituto Federal de Minas Gerais, Brazil & Machine Learning Laboratory in Finance and Organizations (LAMFO), Universidade de Brasília (UnB), Brasília, Brazil
  • Silvia A. dos Reis Business Department, Universidade de Brasília (UnB), Brazil
  • Li Weigang Computer Science Department, Universidade de Brasília (UnB), Brazil
  • Victor R. R. Celestino Business Department, Universidade de Brasília (UnB), Brazil & Machine Learning Laboratory in Finance and Organizations (LAMFO), Universidade de Brasília (UnB), Brasília, Brazil

DOI:

https://doi.org/10.31577/cai_2024_5_1185

Keywords:

Machine learning, natural language processing, summarization

Abstract

Automatic Text Summarization (ATS) is a fundamental aspect of Natural Language Processing (NLP) that allows for the conversion of lengthy text documents into concise summaries that retain the essential information based on specific criteria. In this paper, we present a literature review on the topic of ATS, which includes an overview of the various approaches to ATS, categorized by the mechanisms they use to generate a summary. By organizing these approaches based on their underlying mechanisms, we provide a comprehensive understanding of the current state-of-the-art in ATS systems.

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Published

2024-10-31

How to Cite

Cajueiro, D. O., G. Nery, A., Tavares, I., K. De Melo, M., A. dos Reis, S., Weigang, L., & R. R. Celestino, V. (2024). A comprehensive review of automatic text summarization techniques. Computing and Informatics, 43(5), 1185–1218. https://doi.org/10.31577/cai_2024_5_1185

Issue

Vol. 43 No. 5 (2024): Computing and Informatics

Section

Articles