Natural Language Generation

dc.contributor.author	Sido, Jakub
dc.date.accessioned	2021-04-09T06:03:12Z
dc.date.available	2021-04-09T06:03:12Z
dc.date.issued	2020
dc.description.abstract-translated	Computational systems use natural language for communication with humans moreoften in the last years. This work summarises state-of-the-art approaches in thefield of generative models, especially in the text domain. It offers a complex study ofspecific problems known from this domain and related ones like adversarial training,reinforcement learning, artificial neural networks, etc. It also addresses the usageof these models in the context of non-generative approaches and the possibility ofcombining both.	en
dc.description.sponsorship	GS-2019-018 Processing of heterogeneousdata and its specialized applications	en
dc.format	56 s.	cs
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/11025/43167
dc.identifier.uri	https://www.kiv.zcu.cz/cz/vyzkum/publikace/technicke-zpravy/
dc.language.iso	en	en
dc.publisher	University of West Bohemia	en
dc.rights	© 2020 University of West Bohemia	en
dc.rights.access	openAccess	en
dc.subject	přirozený jazyk	cs
dc.subject	generativní modely	cs
dc.subject	textová doména	cs
dc.subject	umělé neuronové sítě	cs
dc.subject.translated	natural language	en
dc.subject.translated	generative models	en
dc.subject.translated	text domain	en
dc.subject.translated	artificial neural networks	en
dc.title	Natural Language Generation	en
dc.type	zpráva	cs
dc.type	report	en
dc.type.version	publishedVersion	en

Files

Showing 1 - 1 out of 1 results

Showing 1 - 1 out of 1 results