Kazan (Volga region) Federal University, KFU
KAZAN
FEDERAL UNIVERSITY
 
COMPUTING RUSSIAN MORPHOLOGICAL DISTRIBUTION PATTERNS USING RUSAC ONLINE SERVER
Form of presentationArticles in international journals and collections
Year of publication2020
Языканглийский
  • Danilov Andrey Vladimirovich, author
  • Martynova Ekaterina Vladimirovna, author
  • Solnyshkina Marina Ivanovna, author
  • Solovev Valeriy Dmitrievich, author
  • Yarmakeev Iskander Engelevich, author
  • Bibliographic description in the original language Gatiyatullina G, Solnyshkina M, Solovyev V, Computing Russian Morphological distribution patterns using RusAC Online Server//Proceedings - International Conference on Developments in eSystems Engineering, DeSE. - 2020. - Vol.2020-December, Is.. - P.393-398.
    Annotation The article presents findings of distribution patterns of Russian grammatical categories computed with the help of MyStem.3 tagger and a proprietary Russian language processor, ETAP-3. The corpus of over 1.1 mln tokens compiled for the study comprises two types of academic texts used in Russian schools: Science textbooks and Humanities textbooks. We computed descriptive metrics of each textbooks with the help of the text analyzer RusAC (http://tykau.pythonanywhere.com/) and pursued the contrastive analysis of Science and Humanities classroom textbook features. Significant differences of two types of the texts were found in distribution patterns of noun cases and verbs tenses, while morphological patterns of nouns, adjectives, verbs, adverbs demonstrate similarities. The specifics of grammatical patterns defined for classroom textbooks can be used in further studies on distribution of morphological patterns and text complexity of Russian academic texts
    Keywords corpus linguistics , types of texts , genres , academic register , text complexity , morphological distribution , distribution patterns
    The name of the journal Proceedings - International Conference on Developments in eSystems Engineering, DeSE
    URL https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112528662&doi=10.1109%2fDeSE51703.2020.9450753&partnerID=40&md5=abbf3d28786c92ebb3734d70a05da0f1
    Please use this ID to quote from or refer to the card https://repository.kpfu.ru/eng/?p_id=255767&p_lang=2

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