@inproceedings{cardon-etal-2024-contribution-move,
title = "Contribution of Move Structure to Automatic Genre Identification: An Annotated Corpus of {F}rench Tourism Websites",
author = "Cardon, R{\'e}mi and
Pham, Trang Tran Hanh and
Zakhia Doueihi, Julien and
Fran{\c{c}}ois, Thomas",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.347",
pages = "3916--3926",
abstract = "The present work studies the contribution of move structure to automatic genre identification. This concept - well known in other branches of genre analysis - seems to have little application in natural language processing. We describe how we collect a corpus of websites in French related to tourism and annotate it with move structure. We conduct experiments on automatic genre identification with our corpus. Our results show that our approach for informing a model with move structure can increase its performance for automatic genre identification, and reduce the need for annotated data and computational power.",
}
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<abstract>The present work studies the contribution of move structure to automatic genre identification. This concept - well known in other branches of genre analysis - seems to have little application in natural language processing. We describe how we collect a corpus of websites in French related to tourism and annotate it with move structure. We conduct experiments on automatic genre identification with our corpus. Our results show that our approach for informing a model with move structure can increase its performance for automatic genre identification, and reduce the need for annotated data and computational power.</abstract>
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%0 Conference Proceedings
%T Contribution of Move Structure to Automatic Genre Identification: An Annotated Corpus of French Tourism Websites
%A Cardon, Rémi
%A Pham, Trang Tran Hanh
%A Zakhia Doueihi, Julien
%A François, Thomas
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F cardon-etal-2024-contribution-move
%X The present work studies the contribution of move structure to automatic genre identification. This concept - well known in other branches of genre analysis - seems to have little application in natural language processing. We describe how we collect a corpus of websites in French related to tourism and annotate it with move structure. We conduct experiments on automatic genre identification with our corpus. Our results show that our approach for informing a model with move structure can increase its performance for automatic genre identification, and reduce the need for annotated data and computational power.
%U https://aclanthology.org/2024.lrec-main.347
%P 3916-3926
Markdown (Informal)
[Contribution of Move Structure to Automatic Genre Identification: An Annotated Corpus of French Tourism Websites](https://aclanthology.org/2024.lrec-main.347) (Cardon et al., LREC-COLING 2024)
ACL