Comprehensive Review of Automatic Text Summarization Techniques

Daniel O. Cajueiro; Arthur G. Nery; Igor Tavares; Maísa K. De Melo; Silvia A. dos Reis

doi:10.31577/cai_2024_5_1185

¹Department 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

²Department of Economics, Universidade de Brasília (UnB), Brazil & Machine Learning Laboratory in Finance and Organizations (LAMFO) Universidade de Brasília (UnB), Brasília, Brazil

³Mechanic Engineering Department, Universidade de Brasília (UnB), Brazil

⁴Department of Mathematics, Instituto Federal de Minas Gerais, Brazil & Machine Learning Laboratory in Finance and Organizations (LAMFO) Universidade de Brasília (UnB), Brasília, Brazil

⁵Business Department, Universidade de Brasília (UnB), Brazil

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.

Keywords

MSC

68Txx, 68Uxx

Cite this article

@article{cai-6566,
  author  = {Daniel O. Cajueiro and Arthur G. Nery and Igor Tavares and Maísa K. De Melo and Silvia A. dos Reis},
  title   = {Comprehensive Review of Automatic Text Summarization Techniques},
  journal = {Computing and Informatics},
  volume  = {43},
  number  = {5},
  pages   = {1185--1218},
  year    = {2024},
  issn    = {1335-9150},
  doi     = {10.31577/cai_2024_5_1185}
}

Download .bib

TY  - JOUR
AU  - Daniel O. Cajueiro
AU  - Arthur G. Nery
AU  - Igor Tavares
AU  - Maísa K. De Melo
AU  - Silvia A. dos Reis
TI  - Comprehensive Review of Automatic Text Summarization Techniques
JO  - Computing and Informatics
VL  - 43
IS  - 5
SP  - 1185
EP  - 1218
PY  - 2024
SN  - 1335-9150
DO  - 10.31577/cai_2024_5_1185
UR  - https://doi.org/10.31577/cai_2024_5_1185
KW  - Machine learning
KW  - natural language processing
KW  - summarization
ER  -

Download .ris

Cajueiro, D. O., Nery, A. G., Tavares, I., Melo, M. K. D., & Reis, S. A. d. (2024). Comprehensive Review of Automatic Text Summarization Techniques. Computing and Informatics, 43(5), 1185–1218. https://doi.org/10.31577/cai_2024_5_1185

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