@inproceedings{costa-paraboni-2019-personality,
title = "Personality-dependent Neural Text Summarization",
author = "Costa, Pablo and
Paraboni, Ivandr{\'e}",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
month = sep,
year = "2019",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/R19-1024",
doi = "10.26615/978-954-452-056-4_024",
pages = "205--212",
abstract = "In Natural Language Generation systems, personalization strategies - i.e, the use of information about a target author to generate text that (more) closely resembles human-produced language - have long been applied to improve results. The present work addresses one such strategy - namely, the use of Big Five personality information about the target author - applied to the case of abstractive text summarization using neural sequence-to-sequence models. Initial results suggest that having access to personality information does lead to more accurate (or human-like) text summaries, and paves the way for more robust systems of this kind.",
}
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<abstract>In Natural Language Generation systems, personalization strategies - i.e, the use of information about a target author to generate text that (more) closely resembles human-produced language - have long been applied to improve results. The present work addresses one such strategy - namely, the use of Big Five personality information about the target author - applied to the case of abstractive text summarization using neural sequence-to-sequence models. Initial results suggest that having access to personality information does lead to more accurate (or human-like) text summaries, and paves the way for more robust systems of this kind.</abstract>
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%0 Conference Proceedings
%T Personality-dependent Neural Text Summarization
%A Costa, Pablo
%A Paraboni, Ivandré
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F costa-paraboni-2019-personality
%X In Natural Language Generation systems, personalization strategies - i.e, the use of information about a target author to generate text that (more) closely resembles human-produced language - have long been applied to improve results. The present work addresses one such strategy - namely, the use of Big Five personality information about the target author - applied to the case of abstractive text summarization using neural sequence-to-sequence models. Initial results suggest that having access to personality information does lead to more accurate (or human-like) text summaries, and paves the way for more robust systems of this kind.
%R 10.26615/978-954-452-056-4_024
%U https://aclanthology.org/R19-1024
%U https://doi.org/10.26615/978-954-452-056-4_024
%P 205-212
Markdown (Informal)
[Personality-dependent Neural Text Summarization](https://aclanthology.org/R19-1024) (Costa & Paraboni, RANLP 2019)
ACL
- Pablo Costa and Ivandré Paraboni. 2019. Personality-dependent Neural Text Summarization. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 205–212, Varna, Bulgaria. INCOMA Ltd..