Modelling of word usage frequency dynamics using artificial neural network

dc.contributor.author	Maslennikova Y.
dc.contributor.author	Bochkarev V.
dc.contributor.author	Voloskov D.
dc.date.accessioned	2018-09-18T20:25:03Z
dc.date.available	2018-09-18T20:25:03Z
dc.date.issued	2014
dc.identifier.issn	1742-6588
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/139670
dc.description.abstract	In this paper the method for modelling of word usage frequency time series is proposed. An artificial feedforward neural network was used to predict word usage frequencies. The neural network was trained using the maximum likelihood criterion. The Google Books Ngram corpus was used for the analysis. This database provides a large amount of data on frequency of specific word forms for 7 languages. Statistical modelling of word usage frequency time series allows finding optimal fitting and filtering algorithm for subsequent lexicographic analysis and verification of frequency trend models. © Published under licence by IOP Publishing Ltd.
dc.relation.ispartofseries	Journal of Physics: Conference Series
dc.title	Modelling of word usage frequency dynamics using artificial neural network
dc.type	Conference Paper
dc.relation.ispartofseries-issue	1
dc.relation.ispartofseries-volume	490
dc.collection	Публикации сотрудников КФУ
dc.source.id	SCOPUS17426588-2014-490-1-SID84896975330

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Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.