Abstract
In this work, we present a method for content selection and document planning for automated news and report generation from structured statistical data such as that offered by the European Union’s statistical agency, EuroStat. The method is driven by the data and is highly topic-independent within the statistical dataset domain. As our approach is not based on machine learning, it is suitable for introducing news automation to the wide variety of domains where no training data is available. As such, it is suitable as a low-cost (in terms of implementation effort) baseline for document structuring prior to introduction of domain-specific knowledge.- Anthology ID:
- 2021.nodalida-main.11
- Volume:
- Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)
- Month:
- May 31--2 June
- Year:
- 2021
- Address:
- Reykjavik, Iceland (Online)
- Editors:
- Simon Dobnik, Lilja Øvrelid
- Venue:
- NoDaLiDa
- SIG:
- Publisher:
- Linköping University Electronic Press, Sweden
- Note:
- Pages:
- 101–111
- Language:
- URL:
- https://aclanthology.org/2021.nodalida-main.11
- DOI:
- Cite (ACL):
- Leo Leppänen and Hannu Toivonen. 2021. A Baseline Document Planning Method for Automated Journalism. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), pages 101–111, Reykjavik, Iceland (Online). Linköping University Electronic Press, Sweden.
- Cite (Informal):
- A Baseline Document Planning Method for Automated Journalism (Leppänen & Toivonen, NoDaLiDa 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2021.nodalida-main.11.pdf