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Authors: Vinícius da Silva ; João Paulo Papa and Kelton Augusto Pontara da Costa

Affiliation: São Paulo State University - UNESP, Bauru, Brazil

Keyword(s): NLP, Text Summarization, Interpretable Learning.

Abstract: Automatic Text Summarization (ATS) is becoming relevant with the growth of textual data; however, with the popularization of public large-scale datasets, some recent machine learning approaches have focused on dense models and architectures that, despite producing notable results, usually turn out in models difficult to interpret. Given the challenge behind interpretable learning-based text summarization and the importance it may have for evolving the current state of the ATS field, this work studies the application of two modern Generalized Additive Models with interactions, namely Explainable Boosting Machine and GAMI-Net, to the extractive summarization problem based on linguistic features and binary classification.

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Paper citation in several formats:
da Silva, V.; Papa, J. and Pontara da Costa, K. (2023). Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 737-745. DOI: 10.5220/0011664100003417

@conference{visapp23,
author={Vinícius {da Silva}. and João Paulo Papa. and Kelton Augusto {Pontara da Costa}.},
title={Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={737-745},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011664100003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection
SN - 978-989-758-634-7
IS - 2184-4321
AU - da Silva, V.
AU - Papa, J.
AU - Pontara da Costa, K.
PY - 2023
SP - 737
EP - 745
DO - 10.5220/0011664100003417
PB - SciTePress

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