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Authors: Oleksandra Klymenko ; Daniel Braun and Florian Matthes

Affiliation: Technical University of Munich, Department of Informatics, Munich, Germany

Keyword(s): Text Summarization, Natural Language Generation, Summary Evaluation.

Abstract: Despite the progress that has been achieved in over 50 years of research, automatic text summarization systems are still far from perfect, posing many challenges to the researchers in the field. This paper provides an overview of the most prominent algorithms for automatic text summarization that were proposed in the last years, as well as describes automatic and manual evaluation methods that are currently widely adopted.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Klymenko, O.; Braun, D. and Matthes, F. (2020). Automatic Text Summarization: A State-of-the-Art Review. In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-423-7; ISSN 2184-4992, SciTePress, pages 648-655. DOI: 10.5220/0009723306480655

@conference{iceis20,
author={Oleksandra Klymenko. and Daniel Braun. and Florian Matthes.},
title={Automatic Text Summarization: A State-of-the-Art Review},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2020},
pages={648-655},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009723306480655},
isbn={978-989-758-423-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Automatic Text Summarization: A State-of-the-Art Review
SN - 978-989-758-423-7
IS - 2184-4992
AU - Klymenko, O.
AU - Braun, D.
AU - Matthes, F.
PY - 2020
SP - 648
EP - 655
DO - 10.5220/0009723306480655
PB - SciTePress