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Encyclopedia of Database Systems pp 4073–4075Cite as

Text Generation

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Synonyms

Natural language generation (NLG)

Definition

Text generation is a subfield of natural language processing. It leverages knowledge in computational linguistics and artificial intelligence to automatically generate natural language texts, which can satisfy certain communicative requirements.

Historical Background

Research work in the text generation field first appeared in the 1970s. Goldman’s work on natural language generation from a deep conceptual base appeared in [2]. In the 1980s, more significant work was contributed in this field: McDonald saw text generation as a decision-making problem [6] and Appelt on language planning (1981) (McKeown [8]). In the 1990s, a generic architecture for text generation was discussed (Reiter [10], Hovy [3]). Still today, variations on the generic architecture is still a widely discussed question (Mellish et al. [9]).

Foundations

Text generation, or natural language generation (NLG), is usually compared with another subfield of natural...

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Recommended Reading

  1. Dale R. Introduction to the special issue on natural language generation. Comput Linguist. 1998;24(3):346–53.

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  2. Goldman NM. Computer generation of natural language from a deep conceptual base. PhD thesis, Stanford University, 1974.

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  3. Hovy EH, Varile GB, Zampolli A. Language generation. Chapter 4. In: Survey of the state of the art in human language Technology. Cambridge: Cambridge University Press; 1997. p. 139–63.

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  4. Hovy EH. Natural language generation. Entry for MIT encyclopedia of computer science. Cambridge: MIT Press; 1998. p. 585–8.

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  5. Hovy EH. Language generation. Entry for encyclopedia of cognitive science, article 86. London: McMillan; 2000.

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  6. McDonald DD. Natural language production as a process of decision making under constraint. PhD thesis, Cambridge: MIT Artificial Intelligence Laboratory; 1980.

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  7. McDonald DD, Dale RH, Moisl H. Somers 1Natural language generation, Chapter 7. In: Handbook of natural language processing. New York: Marcel Dekker; 2000. p. 147–80.

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  8. McKeown KR. Text generation: using discourse strategies and focus constraints to generate natural language text. Cambridge: Cambridge University Press; 1985.

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  9. Mellish C et al. A reference architecture for natural language generation systems. Nat Lang Eng. 2006;12(1):1–34.

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  10. Reiter E. Has a consensus NL generation architecture appeared and is it psycholinguistically plausible? In: Proceedings of the 7th International Conference on Natural Language Generation; 1994. p. 163–170.

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  11. Reiter E, Dale R. Building natural language generation systems. Cambridge: Cambridge University Press; 2000.

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Author information

Authors and Affiliations

  1. Peking University, Beijing, China

    Li Zhang

  2. Microsoft Research Asia, Beijing, China

    Jian-Tao Sun

Authors
  1. Li Zhang
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  2. Jian-Tao Sun
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Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Microsoft Research Asia, Microsoft Corporation, Beijing, Haidian, China

    Zheng Chen

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Zhang, L., Sun, JT. (2018). Text Generation. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_416

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