A classification-based approach to economic event detection in Dutch news text
- Author
- Els Lefever (UGent) and Veronique Hoste (UGent)
- Organization
- Abstract
- Breaking news on economic events such as stock splits or mergers and acquisitions has been shown to have a substantial impact on the financial markets. As it is important to be able to automatically identify events in news items accurately and in a timely manner, we present in this paper proof-of-concept experiments for a supervised machine learning approach to economic event detection in newswire text. For this purpose, we created a corpus of Dutch financial news articles in which 10 types of company-specific economic events were annotated. We trained classifiers using various lexical, syntactic and semantic features. We obtain good results based on a basic set of shallow features, thus showing that this method is a viable approach for economic event detection in news text.
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-7242360
- MLA
- Lefever, Els, and Veronique Hoste. “A Classification-Based Approach to Economic Event Detection in Dutch News Text.” LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, ELRA, 2016, pp. 330–35.
- APA
- Lefever, E., & Hoste, V. (2016). A classification-based approach to economic event detection in Dutch news text. LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 330–335. ELRA.
- Chicago author-date
- Lefever, Els, and Veronique Hoste. 2016. “A Classification-Based Approach to Economic Event Detection in Dutch News Text.” In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 330–35. ELRA.
- Chicago author-date (all authors)
- Lefever, Els, and Veronique Hoste. 2016. “A Classification-Based Approach to Economic Event Detection in Dutch News Text.” In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 330–335. ELRA.
- Vancouver
- 1.Lefever E, Hoste V. A classification-based approach to economic event detection in Dutch news text. In: LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION. ELRA; 2016. p. 330–5.
- IEEE
- [1]E. Lefever and V. Hoste, “A classification-based approach to economic event detection in Dutch news text,” in LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, Portoroz, SLOVENIA, 2016, pp. 330–335.
@inproceedings{7242360,
abstract = {{Breaking news on economic events such as stock splits or mergers and acquisitions has been shown to have a substantial impact on the financial markets. As it is important to be able to automatically identify events in news items accurately and in a timely manner, we present in this paper proof-of-concept experiments for a supervised machine learning approach to economic event detection in newswire text. For this purpose, we created a corpus of Dutch financial news articles in which 10 types of company-specific economic events were annotated. We trained classifiers using various lexical, syntactic and semantic features. We obtain good results based on a basic set of shallow features, thus showing that this method is a viable approach for economic event detection in news text.}},
author = {{Lefever, Els and Hoste, Veronique}},
booktitle = {{LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION}},
isbn = {{9782951740891}},
language = {{eng}},
location = {{Portoroz, SLOVENIA}},
pages = {{330--335}},
publisher = {{ELRA}},
title = {{A classification-based approach to economic event detection in Dutch news text}},
year = {{2016}},
}