• Eva Rakovská University of Economics in Bratislava, Faculty of Economic Informatics, Department of Applied Informatics




assessment, ranking, fuzzy aggregation, knowledge discovery in databases


Today, businesses depend strongly on data and the opinion of customers or the experience of managers or experts. The large databases contain non-heterogeneous data, which is the ground for further decisions. Business uses multicriterial decisions in more areas (e.g., customer care, marketing, product development, risk management, HR, etc.) and often it is based on assessment. One of the assessment methods is the ranking, which can be done by crisp values of data where the sharp borders between evaluated entities do not give the adequate ranking result. On the other hand, the ranking process is based on the qualitative assessment, which has linguistic expression. It is more familiar and understandable for people. The article shows how to treat non-heterogeneous data to prepare them for a ranking process using fuzzy sets theory. The article aims at offering several types of ranking methods based on different inputs and preferences of the user and describes appropriate fuzzy aggregations for solving the ranking problem.


Beliakov, G., Pradera, A., & Calvo S. T. (2007). Aggregation Functions: A Guide for Practitioners. Springer-Verlag,

Berlin, Heidelberg

Beliakov, G. (2009, July) Introduction to fuzzy systems and aggregation operators. [Web presentation post]. Retrieved from https://iemae.upc.edu/ca/seminari-del-institut/realitzats/conf.beliakov.22.07.09

Bhasin, H. (2008, December 22) Top 10 Types of Assessment. [Web article]. Retrieved from https://www.marketing91.com/types-of-assessment/

Cambridge Dictionary (2021). Assessment. Ranking. [Web dictionary post] Retrieved from https://dictionary.cambridge.org/dictionary/english

Herrera, F., & Martinez, L. (2001). A model based on linguistic 2-tuples for dealing with multi granular hierarchical linguistic contexts in multi-expert decision-making. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 31(2), 227–234. https://doi.org/10.1109/3477.915345

Hudec, M., & Vuc̆etić Miljan. (2019). Aggregation of Fuzzy Conformances. New Trends in Aggregation Theory, 302–314. https://doi.org/10.1007/978-3-030-19494-9_28

Lexico Oxford Dictionary (2021). Ranking. [Web dictionary post] Retrieved from https://www.lexico.com/definition/ranking

Likert, R. (1932). A technique for the measurement of attitudes, Archives of Psychology 22(140): 1–55

Pey, J.L.L. (2015, November 6). What are the differences between Sorting and Ranking? [Web blog post]. Retrieved from https://www.quora.com/What-are-the-differences-between-Sorting-and-Ranking

Rakovská, E., & Hudec, M. (2019). A Three-Level Aggregation Model for Evaluating Software Usability by Fuzzy Logic. International Journal of Applied Mathematics and Computer Science, 29(3), 489–501. https://doi.org/10.2478/amcs-2019-0036

Rakovská, E., & Hudec, M. (2019). Two Approaches for the Computational Model for Software Usability in Practice. Advances in Intelligent Systems and Computing, 191–202. https://doi.org/10.1007/978-3-030-18058-4_15

Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N. R., Van de Velde, W., & Wielinga, B. J. (1999). Knowledge Engineering and Management. https://doi.org/10.7551/mitpress/4073.001.0001

Skowron, A., Jankowski, A., & Swiniarski, R. W. (2015). Foundations of Rough Sets. Springer Handbook of Computational Intelligence, 331–348. https://doi.org/10.1007/978-3-662-43505-2_21

Skowron, A., & Dutta, S. (2018). Rough sets: past, present, and future. Natural Computing, 17(4), 855–876. https://doi.org/10.1007/s11047-018-9700-3

Sojka, P., Hudec, M., & Švaňa, M. (2020). Linguistic Summaries in Evaluating Elementary Conditions, Summarizing Data and Managing Nested Queries. Informatica, 1–16. https://doi.org/10.15388/20-infor428

Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8, 338–353 https://doi.org/10.1016/S0019-9958(65)90241-X




How to Cite

Rakovská, E. . (2021). FUZZY AGGREGATION FOR RANKING IN BUSINESS. Proceedings of CBU in Economics and Business, 2, 81-87. https://doi.org/10.12955/peb.v2.258