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Detecting document structure in a very large corpus of UK financial reports

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Detecting document structure in a very large corpus of UK financial reports. / El-Haj, Mahmoud; Rayson, Paul; Young, Steven; Walker, Martin.

LREC'14 Ninth International Conference on Language Resources and Evaluation . Reykjavik, Iceland : European Language Resources Association (ELRA), 2014. p. 1335-1338 402 (Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014)).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

El-Haj, M, Rayson, P, Young, S & Walker, M 2014, Detecting document structure in a very large corpus of UK financial reports. in LREC'14 Ninth International Conference on Language Resources and Evaluation ., 402, Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), European Language Resources Association (ELRA), Reykjavik, Iceland, pp. 1335-1338. <http://www.lrec-conf.org/proceedings/lrec2014/pdf/402_Paper.pdf>

APA

El-Haj, M., Rayson, P., Young, S., & Walker, M. (2014). Detecting document structure in a very large corpus of UK financial reports. In LREC'14 Ninth International Conference on Language Resources and Evaluation (pp. 1335-1338). [402] (Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014)). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2014/pdf/402_Paper.pdf

Vancouver

El-Haj M, Rayson P, Young S, Walker M. Detecting document structure in a very large corpus of UK financial reports. In LREC'14 Ninth International Conference on Language Resources and Evaluation . Reykjavik, Iceland: European Language Resources Association (ELRA). 2014. p. 1335-1338. 402. (Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014)).

Author

El-Haj, Mahmoud ; Rayson, Paul ; Young, Steven ; Walker, Martin. / Detecting document structure in a very large corpus of UK financial reports. LREC'14 Ninth International Conference on Language Resources and Evaluation . Reykjavik, Iceland : European Language Resources Association (ELRA), 2014. pp. 1335-1338 (Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014)).

Bibtex

@inproceedings{0eb3e03da10340e4832db9d9ee42064b,
title = "Detecting document structure in a very large corpus of UK financial reports",
abstract = "In this paper we present the evaluation of our automatic methods for detecting and extracting document structure in annual financial reports. The work presented is part of the Corporate Financial Information Environment (CFIE) project in which we are using Natural Language Processing (NLP) techniques to study the causes and consequences of corporate disclosure and financial reporting outcomes.We aim to uncover the determinants of financial reporting quality and the factors that influence the quality of information disclosedto investors beyond the financial statements. The CFIE consists of the supply of information by firms to investors, and the mediatinginfluences of information intermediaries on the timing, relevance and reliability of information available to investors. It is important to compare and contrast specific elements or sections of each annual financial report across our entire corpus rather than working at the full document level. We show that the values of some metrics e.g. readability will vary across sections, thus improving on previous research based on full texts.",
author = "Mahmoud El-Haj and Paul Rayson and Steven Young and Martin Walker",
year = "2014",
language = "English",
isbn = "9782951740884",
series = "Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014)",
publisher = "European Language Resources Association (ELRA)",
pages = "1335--1338",
booktitle = "LREC'14 Ninth International Conference on Language Resources and Evaluation",

}

RIS

TY - GEN

T1 - Detecting document structure in a very large corpus of UK financial reports

AU - El-Haj, Mahmoud

AU - Rayson, Paul

AU - Young, Steven

AU - Walker, Martin

PY - 2014

Y1 - 2014

N2 - In this paper we present the evaluation of our automatic methods for detecting and extracting document structure in annual financial reports. The work presented is part of the Corporate Financial Information Environment (CFIE) project in which we are using Natural Language Processing (NLP) techniques to study the causes and consequences of corporate disclosure and financial reporting outcomes.We aim to uncover the determinants of financial reporting quality and the factors that influence the quality of information disclosedto investors beyond the financial statements. The CFIE consists of the supply of information by firms to investors, and the mediatinginfluences of information intermediaries on the timing, relevance and reliability of information available to investors. It is important to compare and contrast specific elements or sections of each annual financial report across our entire corpus rather than working at the full document level. We show that the values of some metrics e.g. readability will vary across sections, thus improving on previous research based on full texts.

AB - In this paper we present the evaluation of our automatic methods for detecting and extracting document structure in annual financial reports. The work presented is part of the Corporate Financial Information Environment (CFIE) project in which we are using Natural Language Processing (NLP) techniques to study the causes and consequences of corporate disclosure and financial reporting outcomes.We aim to uncover the determinants of financial reporting quality and the factors that influence the quality of information disclosedto investors beyond the financial statements. The CFIE consists of the supply of information by firms to investors, and the mediatinginfluences of information intermediaries on the timing, relevance and reliability of information available to investors. It is important to compare and contrast specific elements or sections of each annual financial report across our entire corpus rather than working at the full document level. We show that the values of some metrics e.g. readability will vary across sections, thus improving on previous research based on full texts.

M3 - Conference contribution/Paper

SN - 9782951740884

T3 - Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014)

SP - 1335

EP - 1338

BT - LREC'14 Ninth International Conference on Language Resources and Evaluation

PB - European Language Resources Association (ELRA)

CY - Reykjavik, Iceland

ER -