Nothing Special   »   [go: up one dir, main page]

Skip to main content

On the Applicability of the Modernized Method of Latent-Semantic Analysis to Identify Negative Content in Multimedia Objects

  • Conference paper
  • First Online:
Intelligent Distributed Computing XIII (IDC 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 868))

Included in the following conference series:

  • 891 Accesses

Abstract

The possibility of applying a modernized method of latent semantic analysis (MLSA) to identify negative content in multimedia objects of web space is considered. A method for analyzing the dynamics of changes in the singular numbers of the original matrix with automatic selection of the range of used rank values is described. The positive dynamics of application of the MLSA method in different directions is shown, where semantic analysis of information is required.

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

Access this chapter

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 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover 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. Bermudes, S.H.G., Kerimova, S.U.: O metode opredeleniy tekstovoi blizosti, osnovannom na semanticheskix klassax. Elect. nauchnii jurnal Inzhenernyj vestnik Dona 4(43) [About the method of determination of text closeness based on semantic classes. Electronic science journal Engineering herald of Dona 4(43) (2016). http://www.ivdon.ru/ru/magazine/archive/n4y2016/3832. (in Russian)

  2. Bryant, J., Thompson, S.: Osnovi vozdeistviy SMI. Per. Eng. - Williams, M, p. 432 [Basics of the impact of the media, Translate from English - Williams, M, p. 432] (2004). (in Russian)

    Google Scholar 

  3. Jotsov, V.S., Sgurev, V.S., Yusupov, R.M., Khomonenko, A.D.: Ontologii dly razresheniy semanticheskix konfliktov. In: Trudy SPIIRAN, vol. 7, pp. 26–40 [The Ontology for the Semantic Conflicts Resolution. In: Proceedings of SPIIRAS, vol. 7, pp. 26–40] (2008). (in Russian)

    Google Scholar 

  4. Khomonenko, A.D., Logashev, S.V., Krasnov, S.A.: Avtomaticheskay rubrikaciy dokumentov s pomoch’y lsa algoritma nechetkogo vivoda Mamdami. In: Trudy SPIIRAN, vol. 44, pp. 5–19 [Automatic rubrication of documents using latent-semantic analysis and Mamdani fuzzy inference algorithm. In: Proceedings of SPIIRAS, vol. 44, pp. 5–19] (2015). (in Russian)

    Google Scholar 

  5. Khomonenko, A.D., Krasnov, S.A.: Primenenie metodov latentno-semanticheskogo analiza dly avtomaticheskoi rubrikacii dokumentov. In: Izvestiy Peterburgskogo universiteta putei soobwenii, vol. 31, pp. 124–132 [Application of methods of latent-semantic analysis for automatic document categorization. In: Proceedings of the Petersburg Transport University, vol. 31, pp. 124–132] (2012). (in Russian)

    Google Scholar 

  6. Krasnov, S.A., Ilatovsky, A.S., Khomonenko, A.D., Arsenyev, V.N.: Ocenka semanticheskoi blizosti dokumentov na osnove latentno-semanticheskogo analiza s avtomaticheskim viborom rangovix znachenii. In: Trudy SPIIRAN, vol. 54, pp. 185–204 [Estimation of semantic proximity of documents based on latent-semantic analysis with automatic selection of rank values. In: Proceedings of SPIIRAS, vol. 54, pp. 185–204] (2017). (in Russian)

    Google Scholar 

  7. Krasnov, S.A., Khomonenko, A.D., Dashonok, V.L.: Viyvlenie protivorechii blizkoi informacii na osnove latentno-semanticheskogo analiza. Sbornik nauchnix trudov SPbGPU, vol. 2, pp. 73–84 [Identification of contradictions in semantically close information based on latent-semantic analysis. Collected Scientific Works of the St. Petersburg State Polytechnical University, vol. 2, pp. 73–84] (2014). (in Russian)

    Google Scholar 

  8. Weissman, S., Ayhan, S., Bradley, J., Lin, J.: Identifying duplicate and contradictory information in Wikipedia. In: Proceedings of the 15th ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 57–60 (2015)

    Google Scholar 

  9. Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning Tools and Techniques, 3rd edn., p. 664. Morgan Kaufmann (2011)

    Google Scholar 

Download references

Acknowledgements

The study was carried out with the financial support of the Russian Foundation for Basic Research, project No. 18-29-22064\18.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sergey Krasnov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Krasnov, S., Lokhvitckii, V., Dudkin, A. (2020). On the Applicability of the Modernized Method of Latent-Semantic Analysis to Identify Negative Content in Multimedia Objects. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_27

Download citation

Publish with us

Policies and ethics