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Generation of a dictionary of abstract/concrete words by a multilayer neural network

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dc.contributor.author Solovyev V.D.
dc.contributor.author Bochkarev V.V.
dc.contributor.author Khristoforov S.V.
dc.date.accessioned 2021-02-25T06:52:15Z
dc.date.available 2021-02-25T06:52:15Z
dc.date.issued 2020
dc.identifier.issn 1742-6588
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/161195
dc.description.abstract © Published under licence by IOP Publishing Ltd. Large dictionaries of abstract/concrete words were compiled for several languages by interviewing native speakers. The Russian dictionary contains only one thousand words. This article proposes a new method for automatic generation of a large (tens of thousands of words) Russian dictionary of abstract/concrete words by using neural networks trained on the Google Books Ngram corpus. Estimates of the quality of the dictionary compiled using this method are obtained. The correlation coefficient between the estimates obtained using a neural network for the level of word concreteness and the estimates obtained based on the native speakers‵ responds is 0.778.
dc.relation.ispartofseries Journal of Physics: Conference Series
dc.title Generation of a dictionary of abstract/concrete words by a multilayer neural network
dc.type Conference Paper
dc.relation.ispartofseries-issue 1
dc.relation.ispartofseries-volume 1680
dc.collection Публикации сотрудников КФУ
dc.source.id SCOPUS17426588-2020-1680-1-SID85098559509


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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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