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A Complex Approach to the Data Labeling Efficiency Improvement

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Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19) (IITI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1156))

Abstract

In this paper the issue of labeling noise is considered. Data labeling is the integral stage of the most part of the machine learning projects, so the problem spotlighted in the paper is quite topical.

According to the labeling noise source classification, a new approach is proposed, affecting both of the labeling noise sources. The first component of the approach is based on the distributed ledger technologies principles, including the automatic consensus between the experts. The second component includes the devices dependability improvement by means of fog- and edge-computing usage. Also some models are developed to estimate the approach and selected results of the simulation are presented and discussed.

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Acknowledgements

The paper has been prepared within the RFBR project 18-29-22086 and RAS presidium fundamental research №7 «New designs in the prospective directions of the energetics, mechanics and robotics», № gr.project AAAA-A18-118020190041-1.

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Authors and Affiliations

  1. Federal Research Centre, Southern Scientific Centre of the Russian Academy of Sciences, 41, Chehova st, 344006, Rostov-on-Don, Russia

    E. V. Melnik

  2. Scientific Research Institute of Multiprocessor Computer Systems of Southern Federal University, 2, Chehova st, 347928, Taganrog, Russia

    A. B. Klimenko

Authors
  1. E. V. Melnik
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  2. A. B. Klimenko
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Corresponding author

Correspondence to A. B. Klimenko .

Editor information

Editors and Affiliations

  1. Rostovskogo Strelkovogo Polka Narodnogo, Rostov State Transport University, Rostov-on-Don, Russia

    Sergey Kovalev

  2. Bauman Moscow State Technical University, Moscow, Russia

    Valery Tarassov

  3. Department of Computer Science, VSB-Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Vaclav Snasel

  4. Rostovskogo Strelkovogo Polka, Rostov State Transport University, Rostov-on-Don, Russia

    Andrey Sukhanov

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Melnik, E.V., Klimenko, A.B. (2020). A Complex Approach to the Data Labeling Efficiency Improvement. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_5

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