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A Method of Static and Dynamic Pattern Analysis of Innovative Development of Russian Regions in the Long Run

  • Fuad Aleskerov
  • Ludmila EgorovaEmail author
  • Leonid Gokhberg
  • Alexey Myachin
  • Galina Sagieva
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 104)

Abstract

The term “pattern” refers to a combination of values of some features such that objects with these feature values significantly differ from other objects. This concept is a useful tool for the analysis of behavior of objects in both statics and dynamics. If the panel data describing the functioning of objects in time is available, we can analyze pattern changing behavior of the objects and identify either well adapted to the environment objects or objects with unusual and alarming behavior.In this paper we apply static and dynamic pattern analysis to the analysis of innovative development of the Russian regions in the long run and obtain a classification of regions by the similarity of the internal structure of these indicators and groups of regions carrying out similar strategies.

Keywords

Innovation Activity Innovative Activity Russian Region Innovative Development AIDA System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work is a part of a project of data analysis of science, education, and innovative activity performed by National Research University Higher School of Economics under the state contract No. 07.514.11.4144 “Development of an experimental sample of statistical analysis of science, education, and innovation software using advanced techniques: pattern analysis and data ontological modeling” with Ministry of Education and Science, code 2012-1.4-07-514-0041.

Authors express their sincere gratitude to the Laboratory of Decision Choice and Analysis NRU HSE (F. Aleskerov, L. Egorova, A. Myachin) and Laboratory of Algorithms and Technologies for Network Analysis NRU HSE, Russian Federation Government Grant N. 11.G34.31.0057 (L. Egorova) for partial financial support. The study was undertaken in the framework of the Program of Fundamental Studies of the Higher School of Economics in 2012–2013.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fuad Aleskerov
    • 1
  • Ludmila Egorova
    • 1
    Email author
  • Leonid Gokhberg
    • 1
  • Alexey Myachin
    • 1
  • Galina Sagieva
    • 1
  1. 1.National Research University Higher School of EconomicsMoscowRussia

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