The Linear Estimation Problem and Information in Big-Data Systems

Information Analysis

Abstract

This paper addresses the problem of transforming the optimal linear estimation procedure in such a way that separate fragments of initial data are processed individually and concurrently. A representation of intermediate information is proposed that allows an algorithm to concurrently extract this information from each initial data set, combine it, and use it for estimation. It is shown that, on an information space constructed, an ordering is induced that reflects the concept of information quality.

Keywords

Big Data linear estimation canonical information distributed data collection and processing systems information algebra and information space 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Golubtsov, P.V., The concept of information in big data processing, Autom. Doc. Math. Linguist., 2018, vol. 52, no. 1, pp. 38–43.CrossRefGoogle Scholar
  2. 2.
    Pyt’ev, Yu.P., Pseudoinverse operators. Properties and applications, Math. USSR Sb., 1983, vol. 46, no. 1, pp. 17–50.MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Pyt’ev, Yu.P., Matematicheskie metody interpretatsii eksperimenta (Mathematical Methods for Experiment Interpretation), Moscow: Vysshaya shkola, 1989.MATHGoogle Scholar
  4. 4.
    Pyt’ev, Yu.P., Reduction problems in experimental investigations, Math. USSR Sb., vol. 48, no. 1, pp. 237–272.Google Scholar
  5. 5.
    Golubtsov, P.V., Informativity in the category of linear measurement systems, Problems Inform. Transmission, 1992, vol. 28, no. 2, pp. 125–140.MathSciNetMATHGoogle Scholar
  6. 6.
    Golubtsov, P.V., Informativity in the Category of Multivalued Information Transformers, Problems Inform. Transmission, vol. 34, no. 3, pp. 259–276.Google Scholar
  7. 7.
    Golubtsov, P.V., Axiomatic Description of Categories of Information Transformers, Problems Inform. Transmission, 1999, vol. 35, no. 3, pp. 259–274.MathSciNetMATHGoogle Scholar
  8. 8.
    Golubtsov, P.V., Monoidal Kleisli category as a background for information transformers theory, Inf. Process., 2002, vol. 2, no. 1, pp. 62–84.MATHGoogle Scholar
  9. 9.
    Golubtsov, P.V., Information transformers: Categorytheoretical structure, informativeness, decision-making problems, Hadronic J. Suppl., 2004, vol. 19, no. 4, pp. 375–424.MathSciNetMATHGoogle Scholar
  10. 10.
    Golubtsov, P.V. and Filatova, S.A., Multivalued measuring and computing systems, Mat. Model., 1992, vol. 4, no. 7, pp. 79–94.MathSciNetMATHGoogle Scholar
  11. 11.
    Golubtsov, P.V., Theory of Fuzzy Sets as a Theory of Uncertainty and Decision-Making Problems in Fuzzy Experiments, Problems Inform. Transmission, 1995, vol. 30, no. 3, pp. 232–250.MathSciNetMATHGoogle Scholar

Copyright information

© Allerton Press, Inc. 2018

Authors and Affiliations

  1. 1.Lomonosov Moscow State UniversityMoscowRussia
  2. 2.National Research University Higher School of EconomicsMoscowRussia

Personalised recommendations