Abstract
This chapter is about natural language texts generated automatically. We will discuss the motivation as to why these texts are needed and discuss which domains will profit from such texts. During recent years NLG technology has matured. Millions of news articles are generated daily. However, there is potential for higher quality and more elaborated styles. For this purpose, new techniques have to be developed. These techniques need to be semantically driven. As examples, we will discuss (a) the use and the retrieval of background information by following paths in knowledge graphs, (b) how to calculate and exploit information structure, and (c) how to hyper-personalise automatically generated news.
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Bense, H., Schade, U., Dembach, M. (2018). Generating Natural Language Texts. In: Hoppe, T., Humm, B., Reibold, A. (eds) Semantic Applications. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55433-3_6
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DOI: https://doi.org/10.1007/978-3-662-55433-3_6
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