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Previous issue (2021. Vol. 11, no. 1)

Modelling and Data Analysis

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 2219-3758

ISSN (online): 2311-9454

DOI: https://doi.org/10.17759/mda

License: CC BY-NC 4.0

Started in 2011

Published 4 times a year

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Automatiс Recommendation of Video for Online School Lesson Using Neuro-Linguistic Programming 54

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Smirnov D.A.
Undergraduate Student of the Institute of Information Technology and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia
ORCID: https://orcid.org/0000-0002-7092-2612
e-mail: daniil.smirnov2311@yandex.ru

Sologub G.B.
PhD in Physics and Matematics, Associate Professor of the Department of Mathematical Cybernetics of Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia
ORCID: https://orcid.org/0000-0002-5657-4826
e-mail: glebsologub@ya.ru

Abstract
The article describes an approach to automating the matching of video materials to text slides in English classes in an online school by vectorizing slide text and video subtitles using the TF-IDF measure and maximizing the cosine similarity measure of these vector representations.

Keywords: teaching automation, distance learning, text similarity

Column: Teaching Methodology

DOI: https://doi.org/10.17759/mda.2020100208

For Reference

References
  1. Daniel Jurafsky, James H. Martin. Speech and Language Processing. An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Second Edition. Pearson Education International, 2009. 1024 pp.
  2. Friedl, John. Regulyarnye vyrazheniya = Regular Expressions. Piter, 2001. 352 pp. ISBN 5–318–00056–8.
  3. Jones K.S. A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation. MCB University Press, 2004. Vol. 60, no. 5, pp. 493–502. ISSN 0022–0418.
 
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