@inproceedings{giguet-etal-2020-daniel,
title = "Daniel@{F}in{TOC}{'}2 Shared Task: Title Detection and Structure Extraction",
author = {Giguet, Emmanuel and
Lejeune, Ga{\"e}l and
Tanguy, Jean-Baptiste},
editor = "El-Haj, Dr Mahmoud and
Athanasakou, Dr Vasiliki and
Ferradans, Dr Sira and
Salzedo, Dr Catherine and
Elhag, Dr Ans and
Bouamor, Dr Houda and
Litvak, Dr Marina and
Rayson, Dr Paul and
Giannakopoulos, Dr George and
Pittaras, Nikiforos",
booktitle = "Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "COLING",
url = "https://aclanthology.org/2020.fnp-1.30",
pages = "174--180",
abstract = "We present our contributions for the 2020 FinTOC Shared Tasks: Title Detection and Table of Contents Extraction. For the Structure Extraction task, we propose an approach that combines information from multiple sources: the table of contents, the wording of the document, and lexical domain knowledge. For the title detection task, we compare surface features to character-based features on various training configurations. We show that title detection results are very sensitive to the kind of training dataset used.",
}
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<date>2020-12</date>
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%0 Conference Proceedings
%T Daniel@FinTOC’2 Shared Task: Title Detection and Structure Extraction
%A Giguet, Emmanuel
%A Lejeune, Gaël
%A Tanguy, Jean-Baptiste
%Y El-Haj, Dr Mahmoud
%Y Athanasakou, Dr Vasiliki
%Y Ferradans, Dr Sira
%Y Salzedo, Dr Catherine
%Y Elhag, Dr Ans
%Y Bouamor, Dr Houda
%Y Litvak, Dr Marina
%Y Rayson, Dr Paul
%Y Giannakopoulos, Dr George
%Y Pittaras, Nikiforos
%S Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation
%D 2020
%8 December
%I COLING
%C Barcelona, Spain (Online)
%F giguet-etal-2020-daniel
%X We present our contributions for the 2020 FinTOC Shared Tasks: Title Detection and Table of Contents Extraction. For the Structure Extraction task, we propose an approach that combines information from multiple sources: the table of contents, the wording of the document, and lexical domain knowledge. For the title detection task, we compare surface features to character-based features on various training configurations. We show that title detection results are very sensitive to the kind of training dataset used.
%U https://aclanthology.org/2020.fnp-1.30
%P 174-180
Markdown (Informal)
[Daniel@FinTOC’2 Shared Task: Title Detection and Structure Extraction](https://aclanthology.org/2020.fnp-1.30) (Giguet et al., FNP 2020)
ACL