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Previous issue (2022. Vol. 12, no. 2)

Modelling and Data Analysis

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 2219-3758

ISSN (online): 2311-9454


License: CC BY-NC 4.0

Published since 2011

Published 4 times a year

Free of fees
Open Access Journal


Using a Self-Learning Algorithm with Elements of Artificial Intelligence Based on Markov Chains to Correct the Semantic Core 30


kolotovkin I.S.
Elektrostal, Russia

The article discusses the effective use of a software tool with elements of artificial intelligence based on Markov chains. Based on the rich personal experience of the author, a description of typical problems arising in this area is given. This article describes only recommendations for using the algorithm.

Keywords: semantic core, Markov chains, key phrases, artificial intelligence

Column: Short Messages


Received: 03.06.2022

Accepted: 13.06.2022

For Reference

  1. Rykov A.S. Methods of system analysis: Multicriteria and fuzzy optimization, modeling and expert evaluations. — M.: Economics, 1999.
  2. Search Engine Optimization (SEO) Secrets / Danny Dover, Erik Dafforn. — Indianapolis: John Wiley & Sons Limited, 2011.
  3. Kolotovkin I.S., Kulik S.D., Shevchenko A.A., Neural networks in the problems of query clustering when compiling a semantic core //Abstracts. XVII All-Russian Scientific Conference "Neurocomputers and their applications" NKP-2019. Moscow, March 19, 2019 — M .: FGBOU VO MGPPU, 2019. — P. 262-263.
  4. Kelbert M. Ya., Sukhov Yu. M. Probability and statistics in examples and problems. Vol. II: Markov chains as a starting point for the theory of random processes and their applications. — M.: MTSNMO, 2009.

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