IDENTIFICATION OF AUTHORS OF A ECONOMICS-POLITICAL TEXT BY MEANS OF A SYMBOL BIGRAMS

Ilhomjon Qodirov

Authors

 

Soliev O.M. – Candidate of Physical and Mathematical Sciences, Department of  Programming and Information Technologies, Polytechnic Institute of Tajik Technical University

Kosimov O.A. – master student, Department of Programming and Information Technologies, Polytechnic Institute of Tajik Technical University

 

Annotation

 

 It is established that the distribution of the frequency of bigrams in the economic and political works of the Russian language is the identifier of authorship. The possibilities of the classifier Z.D. Usmanov to recognize the author of the text by the frequency of letter bigrams are investigated. A digital portrait and a metric space of works are constructed. Under the assumption of the author’s unique creativity set metric thresholds, which are determined on the basis of classes of “homogeneous” works. The γ-classifier of discrete random variables, which confirmed high efficiency in identifying the authorship of text fragments in works of classical and modern poetry, as well as in modern prose of the Tajik language, is tested for adaptability to the recognition of authorship in economic and political works.

 

Key words

 

 Russian language, economics-political text, bigram, classifier, frequency, statistics, efficiency.

 

References

 

  1. Usmanov Z.D., Kosimov A.A. Rate of bigrams in the Tajik literature. – Reports of Academy of Sciences of the Republic of Tajikistan, 2016, t. 59, № 1 – 2, P. 28 – 32.
  2. Romanov A.S., Shelupanov A.A., Meshcheryakov R.V. Development and a research of mathematical models, techniques and software of information processes at identification of the author of the text. – Tomsk: – V-range, 2011, 188 p.
  3. Usmanov Z.D. N-grams in recognition of uniform texts. – Materials of the 20th scientific and practical seminar “New information technologies in the automated systems”. – Moscow, 2017, P. 52 – 54.
  4. Usmanov Z.D. Qualifier of discrete random variables. – Reports of Academy of Sciences of the Republic of Tajikistan. 2017, t. 60, № 7 – 8, P. 291 – 300.
  5. Usmanov Z.D. Algorithm of control of a klasterizator of discrete random variables. – Reports of Academy of Sciences of the Republic of Tajikistan, 2017, t. 60, № 9, P. 392 – 397.
  6. Burkhanova N.M. Budgetary system of the Russian Federation. – M.: Eksmo, 2007, 32 p.
  7. Burkhanova N.M. Economic geography. Cribs. – M.: Eksmo, 2008, 32 p.
  8. Katasonov V.Yu. America against Russia. – M.: Book world, 2015, 449 p.
  9. Katasonov V.Yu. Anti-crisis. To survive and win. – M.: Algorithm, 2015, 149 p.
  10. Katasonov V.Yu. Fight for ruble. – M.: Book world, 2015, 288 p.
  11. Klimova M.A. Salary. – M.: Tax Bulletin, 2008, 320 p.
  12. Klimova M.A. Profits tax. – M.: Tax Bulletin, 2008, 98 p.
  13. Nikanorov P.S. Intermediary activity. – M.: Tax bulletin, 2008, 320 p.
  14. Nikanorov P.S. Joint activity. – M.: Tax bulletin, 2008, 320 p.
  15. Panchenko T.M. Loans and credits. – M.: Tax bulletin, 2008, 158 p.
  16. Panchenko T.M. Holiday and social payments. – M.: Tax bulletin, 2008, 340 p.
  17. Starikov N.V. Geopolitics. How to do it. – SPb.: St. Petersburg, 2014, 368 p.
  18. Starikov N.V. Nationalization of ruble. – SPb.: St. Petersburg, 2011, 169 p.
  19. Shevchuk D.A. Economy history. – M.: Author, 2009, 305 p.
  20. Shevchuk D.A. World economy. Abstract of lectures. – Rostov-on-Don: Phoenix, 2007, 417 p.

 

Publication date

2023-10-26