Google books ngram: Problems of representativeness and data reliability

dc.contributor.author	Solovyev V.D.
dc.contributor.author	Bochkarev V.V.
dc.contributor.author	Akhtyamova S.S.
dc.date.accessioned	2021-02-25T06:54:14Z
dc.date.available	2021-02-25T06:54:14Z
dc.date.issued	2020
dc.identifier.issn	1865-0929
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/161410
dc.description.abstract	© Springer Nature Switzerland AG 2020. The article discusses representativeness of Google Books Ngram as a multi-purpose corpus. Criticism of the corpus is analysed and discussed. A comparative study of the GBN data and the data obtained using the Russian National Corpus and the General Internet Corpus of Russian is performed to show that the Google Books Ngram corpus can be successfully used for corpus-based studies. A new concept “diachronically balanced corpus” is introduced. Besides, the article describes the problems of word spelling and metadata errors presented in the GBN corpus and proposes possible ways of improving quality of the GBN data.
dc.relation.ispartofseries	Communications in Computer and Information Science
dc.subject	Corpus representativeness
dc.subject	Google Books Ngram
dc.subject	Text corpora
dc.subject	Word frequency
dc.title	Google books ngram: Problems of representativeness and data reliability
dc.type	Conference Paper
dc.relation.ispartofseries-volume	1223 CCIS
dc.collection	Публикации сотрудников КФУ
dc.relation.startpage	147
dc.source.id	SCOPUS18650929-2020-1223-SID85088753247

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