Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Method for Determining Linguometric Coefficient Dynamics of Ukrainian Text Content Authorship

  • Conference paper
  • First Online:
Advances in Intelligent Systems and Computing III (CSIT 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 871))

Included in the following conference series:

Abstract

The article describes the peculiarities of linguometry information technologies usage to determine the linguometric coefficients dynamics of the text content authorship. The linguistic and statistical analysis of the author texts within a certain time period takes advantage of the text content-monitoring based on the NLP methods to determine the set of stop words and to study n-grams. The latter is used in the methods of linguometry and stylometry to determine the linguometric coefficients dynamics of the ownership of the analyzed text to a specific author in percentage points. There is proposed a formal approach to the definition of the author’s style of the Ukrainian text in the article. The experimental results of the proposed method for determining the ownership of the analyzed text to a particular author upon the availability of the reference text fragment are obtained. The study was conducted on the basis of the Ukrainian scientific texts of a technical area.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Khomytska, I., Teslyuk, V.: The method of statistical analysis of the scientific, colloquial, belles-lettres and newspaper styles on the phonological level. In: Advances in Intelligent Systems and Computing, vol. 512, pp. 149–163 (2017)

    Google Scholar 

  2. Khomytska, I., Teslyuk, V.: Specifics of phonostatistical structure of the scientific style in English style system. In: Proceedings of the XIth International Conference on Computer Science and Information Technologies, Lviv, pp. 129–131 (2016)

    Google Scholar 

  3. Kowalska, K., Cai, D., Wade, S.: Sentiment analysis of polish texts. Comput. Commun. Eng. 1(1), 39–41 (2012)

    Article  Google Scholar 

  4. Kotsyba, N.: The current state of work on the Polish-Ukrainian Parallel Corpus. In: Organization and Development of Digital Lexical Resources, pp. 55–60 (2009)

    Google Scholar 

  5. Mobasher, B.: Data mining for web personalization. In: The Adaptive Web, pp. 90–135. Springer, Heidelberg (2007)

    Google Scholar 

  6. Dinucă, C.E., Ciobanu, D.: Web content mining. University of Petroşani, Economics, 85 (2012)

    Google Scholar 

  7. Xu, G., Zhang, Y., Li, L.: Web content mining. In: Web Mining and Social Networking, pp. 71–87. Springer (2011)

    Google Scholar 

  8. Ganesh, J.A.: A comparative study of stemming algorithms. Int. J. Comp. Tech. Appl. 2(6), 1930–1938 (2011)

    Google Scholar 

  9. McGovern, G., Norton, R.: Content Critical. FT Press, Upper Saddle River (2001)

    Google Scholar 

  10. McKeever, S.: Understanding web content management systems: evolution, life cycle and market. Ind. Manag. Data Syst. 103(9), 686–692 (2003)

    Article  Google Scholar 

  11. Rockley, A., Norton, R.: Managing Enterprise Content: A Unified Content Strategy. New Riders Press, Reading (2002)

    Google Scholar 

  12. Mishler, A., Crabb, E.S., Paletz, S., Hefright, B., Golonka, E.: Using structural topic modeling to detect events and cluster Twitter users in the Ukrainian crisis. In: Communications in Computer and Information Science, vol. 528, pp. 639–644 (2015)

    Google Scholar 

  13. Davydov, M., Lozynska, O.: Information system for translation into Ukrainian sign language on mobile devices. In: Proceedings of the International Conference on Computer Science and Information Technologies, Lviv, pp. 48–51 (2017)

    Google Scholar 

  14. Davydov, M., Lozynska, O.: Mathematical method of translation into Ukrainian sign language based on ontologies. In: Advances in Intelligent Systems and Computing, vol. 689, pp. 89–100 (2018)

    Google Scholar 

  15. Davydov, M., Lozynska, O.: Linguistic models of assistive computer technologies for cognition and communication. In: Proceedings of the International Conference on Computer Science and Information Technologies, Lviv, pp. 171–175 (2017)

    Google Scholar 

  16. Mykich, K., Burov, Y.: Uncertainty in situational awareness systems. In: Proceedings of the International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science, pp. 729–732 (2016)

    Google Scholar 

  17. Mykich, K., Burov, Y.: Algebraic framework for knowledge processing in systems. In: Advances in Intelligent Systems and Computing, pp. 217–228 (2017)

    Google Scholar 

  18. Mykich, K., Burov, Y.: Research of uncertainties in situational awareness systems and methods of their processing. East. Eur. J. Enterpr. Technol. 1(79), 19–26 (2016)

    Google Scholar 

  19. Mykich, K., Burov, Y.: Algebraic model for knowledge representation in situational awareness systems. In: Proceedings of the International Conference on Computer Sciences and Information Technologies, Lviv, pp. 165–167 (2016)

    Google Scholar 

  20. Victana. http://victana.lviv.ua

  21. Lytvyn, V., Vysotska, V., Uhryn, D., Hrendus, M., Naum, O.: Analysis of statistical methods for stable combinations determination of keywords identification. East. Eur. J. Enterpr. Technol. 2/2(92), 23–37 (2018)

    Google Scholar 

  22. Lytvyn, V., Pukach, P., Bobyk, I., Vysotska, V.: The method of formation of the status of personality understanding based on the content analysis. East. Eur. J. Enterpr. Technol. 5/2(83), 4–12 (2016)

    Google Scholar 

  23. Lytvyn, V., Vysotska, V., Pukach, P., Brodyak, O., Ugryn, D.: Development of a method for determining the keywords in the slavic language texts based on the technology of web mining. East. Eur. J. Enterpr. Technol. 2/2(86), 4–12 (2017)

    Google Scholar 

  24. Lytvyn, V., Vysotska, V., Pukach, P., Bobyk, I., Uhryn, D.: Development of a method for the recognition of author’s style in the Ukrainian language texts based on linguometry, stylemetry and glottochronology. East. Eur. J. Enterpr. Technol. 4/2(2), 10–18 (2017)

    Google Scholar 

  25. Lytvyn, V., Vysotska, V., Pukach, P., Vovk, M., Ugryn, D.: Method of functioning of intelligent agents, designed to solve action planning problems based on ontological approach. East. Eur. J. Enterpr. Technol. 3/2(87), 11–17 (2017)

    Google Scholar 

  26. Lytvyn, V., Vysotska, V., Chyrun, L., Chyrun, L.: Distance learning method for modern youth promotion and involvement in independent scientific researches. In: Proceedings of the IEEE First International Conference on Data Stream Mining & Processing (DSMP), pp. 269–274 (2016)

    Google Scholar 

  27. Kravets, P.: The game method for orthonormal systems construction. In: The Experience of Designing and Application of CAD Systems in Microelectronics (2007)

    Google Scholar 

  28. Kravets, P., Kyrkalo, R.: Fuzzy logic controller for embedded systems. In: Proceedings of the 5th International Conference on Perspective Technologies and Methods in MEMS Design (2009)

    Google Scholar 

  29. Kravets, P.: Game model of dragonfly animat self-learning. In: Perspective Technologies and Methods in MEMS Design, pp. 195–201 (2016)

    Google Scholar 

  30. Kravets, P.: The control agent with fuzzy logic. In: Perspective Technologies and Methods in MEMS Design, pp. 40–41 (2010)

    Google Scholar 

  31. Basyuk, T.: The main reasons of attendance falling of internet resource. In: X-th International Conference on Computer Science and Information Technologies, Lviv, pp. 91–93 (2015)

    Google Scholar 

  32. Maksymiv, O., Rak, T., Peleshko, D.: Video-based flame detection using LBP-based descriptor: influences of classifiers variety on detection efficiency. Int. J. Intell. Syst. Appl. 9(2), 42–48 (2017)

    Google Scholar 

  33. Peleshko, D., Rak, T., Izonin, I.: Image superresolution via divergence matrix and automatic detection of crossover. Int. J. Intell. Syst. Appl. 8(12), 1–8 (2016)

    Google Scholar 

  34. Bazylyk, O., Taradaha, P., Nadobko, O., Chyrun, L., Shestakevych, T.: The results of software complex OPTAN use for modeling and optimization of standard engineering processes of printed circuit boards manufacturing. In: TCSET, pp. 107–108 (2012)

    Google Scholar 

  35. Bondariev, A., Kiselychnyk, M., Nadobko, O., Nedostup, L., Chyrun, L., Shestakevych, T.: The software complex development for modeling and optimizing of processes of radio-engineering equipment quality providing at the stage of manufacture. In: TCSET, p. 159 (2012)

    Google Scholar 

  36. Teslyuk, V., Beregovskyi, V., Denysyuk, P., Teslyuk, T., Lozynskyi, A.: Development and implementation of the technical accident prevention subsystem for the smart home system. Int. J. Intell. Syst. Appl. 10(1), 1–8 (2018)

    Google Scholar 

  37. Pasichnyk, V., Shestakevych, T.: The model of data analysis of the psychophysiological survey results. In: Advances in Intelligent Systems and Computing, vol. 512, pp. 271–282 (2016)

    Google Scholar 

  38. Zhezhnych, P., Markiv, O.: Linguistic comparison quality evaluation of web-site content with tourism documentation objects. In: Advances in Intelligent Systems and Computing, vol. 689, pp. 656–667 (2018)

    Google Scholar 

  39. Vysotska, V., Rishnyak, I, Chyrun, L.: Analysis and evaluation of risks in electronic commerce. In: 9th International Conference on CAD Systems in Microelectronics, pp. 332–333 (2007)

    Google Scholar 

  40. Chernukha, O., Bilushchak, Y.: Mathematical modeling of random concentration field and its second moments in a semispace with erlangian distribution of layered inclusions. Task Q. 20(3), 295–334 (2016)

    Google Scholar 

  41. Shakhovska, N., Vysotska, V., Chyrun, L.: Features of e-learning realization using virtual research laboratory. In: XIth International Conference on Computer Sciences and Information Technologies, Lviv, pp. 143–148 (2016)

    Google Scholar 

  42. Shakhovska, N., Medykovsky, M., Stakhiv, P.: Application of algorithms of classification for uncertainty reduction. Przeglad Elektrotechniczny 89(4), 284–286 (2013)

    Google Scholar 

  43. Schahovs’ ka, N., Syerov, Y.: Web-community ontological representation using intelligent dataspace analyzing agent. In: 10th International Conference on the Experience of Designing and Application, CADSM 2009, pp. 479–480 (2009)

    Google Scholar 

  44. Shakhovska, N., Vovk, O., Hasko, R., Kryvenchuk, Y.: The method of big data processing for distance educational system. In: Conference on Computer Science and Information Technologies, pp. 461–473. Springer, Cham (2017)

    Chapter  Google Scholar 

  45. Shakhovska, N., Vovk, O., Kryvenchuk, Y.: Uncertainty reduction in Big data catalogue for information product quality evaluation. East. Eur. J. Enterp. Technol. 1(2), 12–20 (2018)

    Google Scholar 

  46. Rashkevych, Y., Peleshko, D., Vynokurova, O., Izonin, I., Lotoshynska, N.: Single-frame image super-resolution based on singular square matrix operator. In: IEEE 1th Ukraine Conference on Electrical and Computer Engineering (UKRCON), pp. 944–948 (2017)

    Google Scholar 

  47. Tkachenko, R., Tkachenko, P., Izonin, I., Tsymbal, Y.: Learning-based image scaling using neural-like structure of geometric transformation paradigm. In: Studies in Computational Intelligence, vol. 730, pp. 537–565 (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Victoria Vysotska, Vasyl Lytvyn & Mariya Hrendus

  2. University Institute of Lisbon, Lisbon, Portugal

    Vitor Basto Fernandes

  3. Silesian University of Technology, Gliwice, Poland

    Vasyl Lytvyn

  4. Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

    Michael Emmerich

Authors
  1. Victoria Vysotska
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vitor Basto Fernandes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vasyl Lytvyn
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael Emmerich
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mariya Hrendus
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Victoria Vysotska .

Editor information

Editors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Natalia Shakhovska

  2. Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, Ukraine

    Mykola O. Medykovskyy

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vysotska, V., Fernandes, V.B., Lytvyn, V., Emmerich, M., Hrendus, M. (2019). Method for Determining Linguometric Coefficient Dynamics of Ukrainian Text Content Authorship. In: Shakhovska, N., Medykovskyy, M. (eds) Advances in Intelligent Systems and Computing III. CSIT 2018. Advances in Intelligent Systems and Computing, vol 871. Springer, Cham. https://doi.org/10.1007/978-3-030-01069-0_10

Download citation

Publish with us

Policies and ethics

Search

Navigation