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Automatic morphological analysis on the material of Russian social media texts

7 pagesPublished: March 18, 2019


Automatic morphological analysis is one of the fundamental and significant tasks of NLP (Natural Language Processing). Due to special features of Internet texts, as they can be both normative texts (news, fiction, nonfiction) and less formal texts (such as blogs and texts from social networks), the morphological tagging has become non-trivial and an actual task. In this paper we describe our experiments in tagging of Internet texts presenting our approach based on deep learning. The new social media test set was created, that allows to compare our system with state-of-the-art open source analyzers on the social media texts material.

Keyphrases: morphological parsing, morphological tagging, Natural Language Processing, neural networks, POS tagging, social media texts, taggers for Russian, Universal Dependencies

In: Gerhard Wohlgenannt, Ruprecht von Waldenfels, Svetlana Toldova, Ekaterina Rakhilina, Denis Paperno, Olga Lyashevskaya, Natalia Loukachevitch, Sergei O. Kuznetsov, Olga Kultepina, Dmitry Ilvovsky, Boris Galitsky, Ekaterina Artemova and Elena Bolshakova (editors). Proceedings of Third Workshop "Computational linguistics and language science", vol 4, pages 11--17

BibTeX entry
  author    = {Alena Fenogenova and Viktor Kazorin and Ilia Karpov and Tatyana Krylova},
  title     = {Automatic morphological analysis  on the material of Russian social media texts},
  booktitle = {Proceedings of Third Workshop "Computational linguistics and language science"},
  editor    = {Gerhard Wohlgenannt and Ruprecht von Waldenfels and Svetlana Toldova and Ekaterina Rakhilina and Denis Paperno and Olga Lyashevskaya and Natalia Loukachevitch and Sergei O. Kuznetsov and Olga Kultepina and Dmitry Ilvovsky and Boris Galitsky and Ekaterina Artemova and Elena Bolshakova},
  series    = {EPiC Series in Language and Linguistics},
  volume    = {4},
  pages     = {11--17},
  year      = {2019},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2398-5283},
  url       = {},
  doi       = {10.29007/dlff}}
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