COMPARISON OF NUMERIC PROPERTIES OF OBJECTS OF DIFFERENT DATA DOMAINS IN RELATIONAL DATABASES
DOI:
https://doi.org/10.18372/1990-5548.56.12943Keywords:
Database, subject domain, model of subject domain, information system, entity instance, numeric type properties, сlustering, k-means, method of histograms.Abstract
The problem of association of models of data domains is considered. It is offered to compare objects of data domains on the basis of values of properties of copies of those objects. Methods of benchmarking properties differ depending on type of scales in which their values are measured. It is offered to compare properties of numerical data type by k-means methods, histograms, and also to check coincidence of the distribution law of values of properties. In conjunction of signs to make the decision on similarity of the compared properties.
References
M. G. Glava and T. P. Vasylieva, ”Major problems and methods of databases integration”, First Independent Scientific Journal, no. 1, pp. 28–32, 2015. (in Russian).
M. Glava and V. Malakhov, ”Information Systems Reengineering Approach Based on the Model of Information Systems Domains”, International Journal of Software Engineering and Computer Systems (IJSECS), vol. 4, no. 1, pp. 95–105, 2018, doi: 10.15282/ijsecs.4.1.2018.8.0041.
M. Glava and E. Malakhov, “Searching Similar Entities in Models of Various Subject Domains Based on the Analysis of Their Tuples”, 2016 International Conference on Electronics and Information Technology (EIT´16), May 23–27, 2016, Odesa, Ukraine, pp. 97–100, 2016, doi: 10.1109/ICEAIT.2016.7501001, EID: 2-s2.0-84979503116.
T. Filatova and M. Glava, “Mathematical Models of Information Manipulation in the Subject Field of Intellectual Production in Educational Institutions”, 2016 International Conference on Electronics and Information Technology (EIT´16), May 23–27, 2016, Odesa, Ukraine, pp. 92–96, 2016, doi: 10.1109/ICEAIT.2016.7501000; EID: 2-s2.0-84979554925.
M. Glava, ”Comparison of the nominal type properties of objects of different subject subdomains in relational databases”, Informatics and Mathematical Methods in Simulation, vol. 6, no. 3, pp. 302-309, 2016. (in Russian).
E. V. Malakhov, G. N. Vostrov and M. G. Mikulinska, ”Methods of subject domains objects properties importance definition”, Refrigeration engineering and Technology, no. 4 (126), pp. 73–77, Odessa, 2010. (in Russian).
B. G. Mirkin, Methods of cluster analysis for decision support: review, Moskow, Publishing house of National Research University "Higher School of Economics", 2011. (in Russian).
K. S. Yershov and T. N. Romanova, ”The analysis and classification of algorithms of clustering”, New information technologies in automated systems, pp. 274–279, 2016. (in Russian).
I. A. Bessmertnyj, A. B. Nugumanova and A. V. Platonov, Intellectual systems. Manual and practical work for SPO, Moskow, Publishing House of Eurite, 2018. (in Russian).
S. I. Solonin, Method of histograms: Manual, M.-Berlin: Direct-Media, 2015. (in Russian).
A. I. Orlov, ”Well-founded criteria of check of absolute uniformity of independent selections”, Factory Laboratory. Diagnostics of Materials, vol. 78, no. 11, pp. 66–70, 2012. (in Russian).
G. V. Rubleva, Mathematical statistics: statistical criterions of check of hypotheses. The methodology for students of full-time courses of technical and engineering specialties, Tyumen, Publishing House of the Tyumen State University, 2014. (in Russian).
Yu. Subkov, ”"Net" and applied mathematics”, access mode: https://function-x.ru. (in Russian).
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