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A method of semantic change detection using diachronic corpora data

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dc.contributor.author Bochkarev V.
dc.contributor.author Shevlyakova A.
dc.contributor.author Solovyev V.
dc.date.accessioned 2021-02-25T06:54:12Z
dc.date.available 2021-02-25T06:54:12Z
dc.date.issued 2020
dc.identifier.issn 1865-0929
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/161404
dc.description.abstract © Springer Nature Switzerland AG 2020. The article proposes a method for detecting semantic change using diachronic corpora data. The method is based on the distributional hypothesis. The analysis is performed using frequencies of syntactic bigrams from the English and Russian sub-corpora of Google Books Ngram. To obtain the word co-occurrence profile in its new meaning, syntactic bigrams that contributed most to the word distribution change are selected and their time series are clustered. The method is tested on a group of English and Russian words which gained new meanings in the 20th century. The obtained results show that the proposed method allows one to detect semantics changes, as well as to determine the time of these changes.
dc.relation.ispartofseries Communications in Computer and Information Science
dc.subject Bigram frequencies
dc.subject Cluster analysis
dc.subject Diachronic corpora
dc.subject Google Books Ngram
dc.subject Semantic changes
dc.title A method of semantic change detection using diachronic corpora data
dc.type Conference Paper
dc.relation.ispartofseries-volume 1086
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 94
dc.source.id SCOPUS18650929-2020-1086-SID85087544154


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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.

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