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A statistical tagger for morphological tagging of Russian language texts

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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.

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Authors and Affiliations

  1. Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia

    V. V. Petrochenkov

  2. Moscow State Institute of Radiotechnics, Electronics, and Automation, Moscow, Russia

    A. O. Kazennikov

Authors
  1. V. V. Petrochenkov
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  2. A. O. Kazennikov
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Additional information

Original Russian Text © V.V. Petrochenkov, A.O. Kazennikov, 2013, published in Avtomatika i Telemekhanika, 2013, No. 10, pp. 154–165.

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Petrochenkov, V.V., Kazennikov, A.O. A statistical tagger for morphological tagging of Russian language texts. Autom Remote Control 74, 1724–1732 (2013). https://doi.org/10.1134/S0005117913100123

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  • DOI: https://doi.org/10.1134/S0005117913100123

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