Conference article

A Baseline Document Planning Method for Automated Journalism

Leo Leppänen

Hannu Toivonen

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Published in: Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), May 31-June 2, 2021.

Linköping Electronic Conference Proceedings 178:11, p. 101-111

NEALT Proceedings Series 45:11, p. 101-111

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Published: 2021-05-21

ISBN: 978-91-7929-614-8

ISSN: 1650-3686 (print), 1650-3740 (online)

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.

Keywords

natural language generation, document planning, content selection, automated journalism

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