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Avtomatika i Telemekhanika, 2013, Issue 10, Pages 154–165 (Mi at6155)  
This article is cited in 2 scientific papers (total in 2 papers)

Topical issue

A statistical tagger for morphological tagging of Russian language texts

V. V. Petrochenkova, A. O. Kazennikovb

a Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
b Moscow State Institute of Radiotechnics, Electronics, and Automation, Moscow, Russia
Full-text PDF (203 kB) Citations (2)
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Abstract: We consider a method of constructing a statistical tagger for automated morphological tagging for Russian language texts. In this method, each word is assigned with a tag that contains information about the part of speech and a full set of the word's morphological characteristics. We employ the set of morphological characteristics used in the SynTagRus corpus whose material has been used to train the tagger. The tagger is based on the SVM (Support Vector Machine) approach. The developed tagger has proven to be efficient and has shown high tagging quality.
Presented by the member of Editorial Board: A. V. Bernshtein

Received: 11.03.2013
English version:
Automation and Remote Control, 2013, Volume 74, Issue 10, Pages 1724–1732
DOI: https://doi.org/10.1134/S0005117913100123
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: V. V. Petrochenkov, A. O. Kazennikov, “A statistical tagger for morphological tagging of Russian language texts”, Avtomat. i Telemekh., 2013, no. 10, 154–165; Autom. Remote Control, 74:10 (2013), 1724–1732
Citation in format AMSBIB
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\by V.~V.~Petrochenkov, A.~O.~Kazennikov
\paper A statistical tagger for morphological tagging of Russian language texts
\jour Avtomat. i Telemekh.
\yr 2013
\issue 10
\pages 154--165
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\jour Autom. Remote Control
\yr 2013
\vol 74
\issue 10
\pages 1724--1732
\crossref{https://doi.org/10.1134/S0005117913100123}
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\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-84886066098}
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  • https://www.mathnet.ru/eng/at/y2013/i10/p154
    • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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    Abstract page:282
    Full-text PDF :98
    References:32
    First page:19
     
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