About: A Hybrid Natural Language Generation System Integrating Rules and Deep Learning Algorithms

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	A Hybrid Natural Language Generation System Integrating Rules and Deep Learning Algorithms
Creator	Wei, Wei Leontidis, Georgios Zhou, Bei
source	ArXiv
abstract	This paper proposes an enhanced natural language generation system combining the merits of both rule-based approaches and modern deep learning algorithms, boosting its performance to the extent where the generated textual content is capable of exhibiting agile human-writing styles and the content logic of which is highly controllable. We also come up with a novel approach called HMCU to measure the performance of the natural language processing comprehensively and precisely.
has issue date	2020-06-15(xsd:dateTime)
has license	arxiv
sha1sum (hex)	de5be844224b0c3d6585b27940b234c4b9ea1a43
resource representing a document's title	A Hybrid Natural Language Generation System Integrating Rules and Deep Learning Algorithms
resource representing a document's body	covid:de5be844224b0c3d6585b27940b234c4b9ea1a43#body_text
is schema:about of	named entity 'HIGHLY' named entity 'APPROACH' named entity 'natural language processing' named entity 'LSTM' named entity 'Scholz' »more»

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