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Analysis of Extractive Text Summarization Methods as a Binary Classification Problem

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International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023) (CISIS 2023, ICEUTE 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 748))

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Abstract

One of the critical challenges for natural language processing methods is the issue of automatic content summarization. The enormous increase in the amount of data delivered to users by news services leads to an overload of information without meaningful content. There is a need to generate an automatic text summary that contains as much essential information as possible while keeping the resulting text smooth and concise. Methods of automatic content summarization fall into two categories: extractive and abstractive. This work converts the task of extractive summarization to a binary classification problem. The research focused on analyzing various techniques for extracting the abstract in a supervised learning manner. The results suggest that this different view of text summarization has excellent potential.

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Notes

  1. 1.

    https://www.kaggle.com/datasets/pariza/bbc-news-summary.

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Acknowledgments

This publication is funded by the National Center for Research and Development within INFOSTRATEG program, number of application for funding: INFOSTRATEG-I/0019/2021-00.

Author information

Authors and Affiliations

  1. Pattern Recognition Team of Department of Computer Systems and Networks, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Joanna Komorniczak, Szymon Wojciechowski & Jakub Klikowski

  2. Bydgoszcz University of Science and Technology, Al. prof. S. Kaliskiego 7, 85-796, Bydgoszcz, Poland

    Rafał Kozik & Michał Choraś

Authors
  1. Joanna Komorniczak
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  2. Szymon Wojciechowski
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  3. Jakub Klikowski
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  4. Rafał Kozik
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  5. Michał Choraś
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Corresponding author

Correspondence to Jakub Klikowski .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. School of Industrial, Computer and Aerospace Engineering, University of Leon, León, Spain

    Hilde Pérez García

  3. Department of Mechanical Engineering, University of La Rioja, Logroño, Spain

    Francisco Javier Martínez de Pisón

  4. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. Applied Computational Intelligence, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  7. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    José Luis Calvo Rolle

  8. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    Héctor Quintián

  9. Faculty of Science, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Komorniczak, J., Wojciechowski, S., Klikowski, J., Kozik, R., Choraś, M. (2023). Analysis of Extractive Text Summarization Methods as a Binary Classification Problem. In: García Bringas, P., et al. International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023). CISIS ICEUTE 2023 2023. Lecture Notes in Networks and Systems, vol 748. Springer, Cham. https://doi.org/10.1007/978-3-031-42519-6_9

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