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Using natural language generation to bootstrap missing Wikipedia articles: A human-centric perspective
2022
Semantic Web Journal
Nowadays natural language generation (NLG) is used in everything from news reporting and chatbots to social media management. Recent advances in machine learning have made it possible to train NLG systems that seek to achieve human-level performance in text writing and summarisation. In this paper, we propose such a system in the context of Wikipedia and evaluate it with Wikipedia readers and editors. Our solution builds upon the ArticlePlaceholder, a tool used in 14 under-resourced Wikipedia
doi:10.3233/sw-210431
fatcat:m3qycfrbnjcthp7yfiispnxyyy