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Assessment of Prospects for the Development of Artificial Intelligence Using the Data Mining Methods

  • E. DoroninaEmail author
  • A. Shiryaev
  • N. Komarov
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 139)

Abstract

At present as well as in long-term perspective, artificial intelligence systems and big data processing technologies able to have drastic influence on economic and social aspects of the society are of critical importance for the development of scientific, engineering and economic potential of any country. In this respect, assessment of the current state and the development outlooks of artificial intelligence systems is a topical issue. This article provides the results of the study of publications as well as research and development works conducted by Russian researchers between 2012 and 2017 in the ‘Artificial Intelligence’ line of research. This article proposes an analytical method for the semantic study of related terms and phrases in textual descriptions of the documents that are forming topical trends of research and their liaisons. Shifts in the subject fields, appearance of new applications for artificial intelligence methods in the period of time under consideration, and a change in the accent of the research works from fundamental (theoretical) to application-oriented kinds of scientific research are demonstrated. This approach combines both qualitative and quantitative methods of analysis and makes it possible to predict prospective areas of study. The results so obtained may be used for the analysis of development of the entire subject field as a whole as well as for individual topical trends and may be of interest for the management of scientific research and development.

Keywords

Scientific and technological development Management of science Text mining Semantic analysis Artificial intelligence 

Notes

Acknowledgments

This research was supported by State assignment of Ministry of Education and Science of the Russian Federation № 26.13287.2018/12.1.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Russian Research Institute of Economics, Politics and Law in Science and TechnologyMoscowRussian Federation

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