Evaluation methods of the results of scientific research activity of scientists based on the analysis of publication citations

Authors

DOI:

https://doi.org/10.15587/1729-4061.2017.103651

Keywords:

citation index, evaluation of scientific research activity, bibliometric indicators, integrated evaluation

Abstract

We propose the method for the evaluation of results of scientific research activity of scientists PR-q. This method allows us to calculate a scalar evaluation of the results of scientific activity. The method is based on determining a number of real coefficients, which determine citation of one scientist in the publications by other scientists. The basis of the method is finding the evaluations by solving a system of linear algebraic equations. In this case, the matrix of the given system consists of the constructed coefficients. The proposed method, in contrast to other known methods of calculating the indices of citation, does not lose information about any citation of the author and of any publication.

We proposed the method, based on the construction of vectors of scalar evaluations for each scientist in a multidimensional metric space. This method implies construction of the ideal point, which consists of scalar evaluations, the best in terms of achieving maximal effectiveness of scientific research activity. The evaluation of each scientist is calculated as a metric distance from the ideal point to the vector of scalar evaluations of the given scientist.

The proposed methods for the evaluation of results of scientific research activity might be used to build the modules for automated systems of evaluation of the results of the work of scientists, effectiveness of conducting scientific research by higher educational institutions

Author Biographies

Andrii Biloshchytskyi, Taras Shevchenko National University of Kyiv Volodymyrska str., 60, Kyiv, Ukraine, 01033

Doctor of Technical Sciences, Professor

Department of Technology Management

Alexander Kuchansky, Kyiv National University of Construction and Architecture Povitroflotsky ave., 31, Kyiv, Ukraine, 03037

PhD, Associate Professor

Department of Cybersecurity and computer engineering

Yurii Andrashko, Uzhhorod National University Narodna sq., 3, Uzhhorod, Ukraine, 88000

Lecturer

Department of System Analysis and Optimization Theory 

Svitlana Biloshchytska, Kyiv National University of Construction and Architecture Povitroflotsky ave., 31, Kyiv, Ukraine, 03037

PhD, Associate Professor

Department of Information Technology Designing and Applied Mathematics

Oleksandr Kuzka, Uzhhorod National University Narodna sq., 3, Uzhhorod, Ukraine, 88000

PhD, Associate Professor

Department of System Analysis and Optimization Theory 

Оlexander Terentyev, State «Research Institute of building production» Lobanovskoho ave., 51, Kyiv, Ukraine, 03037

Doctor of Technical Sciences, Associate Professor

References

  1. Lizunov, P., Biloshchytskyi, A., Biloshchytska, S. (2011). Vector project management of higher educational establishment. Management of Development of Complex Systems, 6, 135–139.
  2. Otradskaya, T., Gogunsky, V. (2016). Development process models for evaluation of performance of the educational establishments. Eastern-European Journal of Enterprise Technologies, 3 (3 (81)), 12–22. doi: 10.15587/1729-4061.2016.66562
  3. Yakovenko, V., Gogunskii, V. (2009). Forecasting the state of the quality management system of educational institution. Research systems and informational technologies, 2, 50–57.
  4. Gogunskii, V., Kolesnikov, O., Kolesnikova, K., Lukianov, D. (2016). "Lifelong learning" is a new paradigm of personnel training in enterprises. Eastern-European Journal of Enterprise Technologies, 4 (2 (82)), 4–10. doi: 10.15587/1729-4061.2016.74905
  5. Sherstyuk, O., Olekh, T., Kolesnikova, K. (2016). The research on role differentiation as a method of forming the project team. Eastern-European Journal of Enterprise Technologies, 2 (3 (80)), 63–68. doi: 10.15587/1729-4061.2016.65681
  6. Koroleva, T. S., Vasiliev, I. A., Torozhkov, I. O. (2014). Evaluation criteria for research Institutes activities. Proceedings of the St. Petersburg Scientific Research Institute of Forestry, 2, 94–111.
  7. Andrashko, Yu., Biloshchytskyi, A., Kuchansky, A., Biloshchytska, S., Lyashchenko, T. (2017). Performance evaluation of teaching staff and universities overview. Management of Development of Complex Systems, 29, 151–159.
  8. Burkov, V., Biloshchytskyi, A., Gogunskii, V. (2013). Parameters citation of scientific publications in scientometric databases. Informatization of higher education, 15, 134–139.
  9. Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences, 102 (46), 16569–16572. doi: 10.1073/pnas.0507655102
  10. Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69 (1), 131–152. doi: 10.1007/s11192-006-0144-7
  11. Zhang, C.-T. (2009). The e-Index, Complementing the h-Index for Excess Citations. PLoS ONE, 4 (5), e5429. doi: 10.1371/journal.pone.0005429
  12. Kosmulski, М. (2006). A new Hirsch-type index saves time and works equally well as the original h-index. International Society for Scientometrics and Informetrics, 4–6.
  13. Egghe, L. (2010). The Hirsch index and related impact measures. Annual Review of Information Science and Technology, 44 (1), 65–114. doi: 10.1002/aris.2010.1440440109
  14. Gagolewski, M., Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174. doi: 10.1016/j.ins.2013.12.004
  15. Page, L., Brin, S., Motwani, R., Winograd, T. (1998). The PageRank Citation Ranking: Bringing Order to the Web. Proceedings of the 7th International World Wide Web Conference. Brisbane, Australia, 161–172.
  16. Avrachenkov, K., Litvak, N., Nemirovsky, D., Osipova, N. (2007). Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient. SIAM Journal on Numerical Analysis, 45 (2), 890–904. doi: 10.1137/050643799
  17. Liao, Q., Jiang, S., Yu, M., Yang, Y., Li, T. (2017). Monte Carlo Based Incremental PageRank on Evolving Graphs. Lecture Notes in Computer Science, 356–367. doi: 10.1007/978-3-319-57454-7_28
  18. Kuchanky, A., Biloshchytskyi, A. (2015). Selective pattern matching method for time-series forecasting. Eastern-European Journal of Enterprise Technologies, 6 (4 (78)), 13–18. doi: 10.15587/1729-4061.2015.54812

Downloads

Published

2017-06-30

How to Cite

Biloshchytskyi, A., Kuchansky, A., Andrashko, Y., Biloshchytska, S., Kuzka, O., & Terentyev О. (2017). Evaluation methods of the results of scientific research activity of scientists based on the analysis of publication citations. Eastern-European Journal of Enterprise Technologies, 3(2 (87), 4–10. https://doi.org/10.15587/1729-4061.2017.103651