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Inform. Primen., 2017, Volume 11, Issue 3, Pages 123–131 (Mi ia493)  

This article is cited in 6 scientific papers (total in 6 papers)

Statistical data as information source for linguistic analysis of Russian connectors

O.  Inkova, N. Popkova

Institute of Informatics Problems, Federal Research Center Computer Science and Control of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333

Abstract: The aim of this paper is to describe statistical data gathered from the supracorpora database (SCDB) of connectors for further analysis of their formal and functional properties. Until now, these properties have usually been described applying semantic analysis, while corpus data, if used at all, have not been subject to statistical processing. It is automatically generated and verifiable information, collected from texts corpora that can be one of the most reliable tools in the analysis of linguistic units, including connectors. The paper shows what statistics one may obtain from the SCDB and how to use it in the linguistic analysis in case of tol'ko, a polyfunctional linguistic unit that can be a part of multicomponent and two-place connectors.

Keywords: annotation of connectors; corpus linguistics; supracorpora databases; parallel texts; statistical data.

Funding Agency Grant Number
Russian Foundation for Basic Research 16-06-00070_
The study has been conducted at the Institute of Informatics Problems, Federal Research Center Computer Science and Control of the Russian Academy of Sciences with financial aid from the Russian Foundation for Basic Research (grant No. 16-06-00070).


DOI: https://doi.org/10.14357/19922264170314

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Received: 11.07.2017
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Citation: O.  Inkova, N. Popkova, “Statistical data as information source for linguistic analysis of Russian connectors”, Inform. Primen., 11:3 (2017), 123–131

Citation in format AMSBIB
\Bibitem{InkPop17}
\by O.~~Inkova, N.~Popkova
\paper Statistical data as information source for linguistic analysis of Russian connectors
\jour Inform. Primen.
\yr 2017
\vol 11
\issue 3
\pages 123--131
\mathnet{http://mi.mathnet.ru/ia493}
\crossref{https://doi.org/10.14357/19922264170314}
\elib{http://elibrary.ru/item.asp?id=29992118}


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    Citing articles on Google Scholar: Russian citations, English citations
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    This publication is cited in the following articles:
    1. I. M. Zatsman, M. G. Kruzhkov, E. Yu. Loschilova, “Metody analiza chastotnosti modelei perevoda konnektorov i obratimost generalizatsii statisticheskikh dannykh”, Sistemy i sredstva inform., 27:4 (2017), 164–176  mathnet  crossref  elib
    2. I. M. Zatsman, “Metodologiya obratimoi generalizatsii v kontekste klassifikatsii informatsionnykh transformatsii”, Sistemy i sredstva inform., 28:2 (2018), 128–144  mathnet  crossref  elib
    3. M. G. Kruzhkov, O. Yu. In'kova, “Statistical analysis of language specificity of connectives based on parallel texts”, Inform. i ee primen., 12:3 (2018), 83–90  mathnet  crossref  elib
    4. N. V. Buntman, O. Yu. In'kova, V. A. Nuriev, “Machine translation of Russian connectives into French: errors and quality failures”, Inform. i ee primen., 12:2 (2018), 105–113  mathnet  crossref  elib
    5. N. V. Buntman, I. M. Zatsman, V. A. Nuriev, A. A. Goncharov, “Kolichestvennyi analiz rezultatov mashinnogo perevoda s ispolzovaniem nadkorpusnykh baz dannykh”, Inform. i ee primen., 12:4 (2018), 96–105  mathnet  crossref  elib
    6. I. M. Zatsman, M. G. Kruzhkov, “Nadkorpusnaya baza dannykh konnektorov: razvitie sistemy terminov proektirovaniya”, Sistemy i sredstva inform., 28:4 (2018), 156–167  mathnet  crossref  elib
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