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10691 |
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|a dc
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|a Perera, R
|e author
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|a Nand, P
|e author
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|a Recent Advances in Natural Language Generation: A Survey and Classification of the Empirical Literature
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|b Slovak Academy of Sciences,
|c 2017-07-26T22:18:42Z.
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|a Computing and Informatics, 36(1), 1-32.
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|a 1335-9150
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|a Natural Language Generation (NLG) is defined as the systematic approach for producing human understandable natural language text based on non-textual data or from meaning representations. This is a significant area which empowers human-computer interaction. It has also given rise to a variety of theoretical as well as empirical approaches. This paper intends to provide a detailed overview and a classification of the state-of-the-art approaches in Natural Language Generation. The paper explores NLG architectures and tasks classed under document planning, micro-planning and surface realization modules. Additionally, this paper also identifies the gaps existing in the NLG research which require further work in order to make NLG a widely usable technology.
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|a OpenAccess
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|a Natural Language Generation
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|a Natural Language Processing
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|a Lexicalization
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|a Journal Article
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|z Get fulltext
|u http://hdl.handle.net/10292/10691
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