Application of semantic models and criteria equivalence of data to increase efficiency func-tioning of economic systems

Authors

  • Ganna Pliekhova Kharkov National Automobile and Highway University, 25, Yaroslava Mudrogo str., Kharkiv, 61002, Ukraine.
  • Olena Alisejko Kharkiv Institute of Radio Electronics, 14, Nauki str., Kharkiv, 61000, Ukraine.
  • Zoia Kochuieva 3National Technical University “Kharkiv Polytechnic Institute”2, Kyrpychova str., 61002, Kharkiv, Ukraine.

DOI:

https://doi.org/10.30977/VEIT.2021.19.0.41

Keywords:

relational database, subject area, parameterized or generic data type, object parameter, attribute, domain

Abstract

Problem. In modern society, the role of modeling as a way of cognizing objects with complex structures is growing. The problem of development of models and criteria of semantic equivalence of data under the condition of their lexical ambiguity in relation to relational databases is considered. This is due to the impossibility or undesirability of conducting an experiment on real objects. Modeling was initially applied in "well" studied subject areas (for which the basic laws of object interaction were already known. This knowledge made it possible to set a priori the class of used models of the subject area and reduce the task to setting the model parameters according to the available experimental data. A fundamental change in the modeling scheme occurred during the transition to the development of modeling systems for "weakly" formalized subject areas, where the structure itself and the class of applicable models must be refined in the course of research. The widespread use of relational DB and their use in a wide variety of applications shows that the relational data model is sufficient for modeling domains. Results. The purpose of developing criteria is to prevent relational algebra operations on attributes with lexical and semantic ambiguity. Methods of developing methods and criteria are based on the use of mathematical methods and the use of modern information technology. The scientific novelty is to solve the problem of semantic comparability of relational relations attributes by means of relational model, which allows to effectively solve problems of prevention of relational algebra operations, which lead to data destruction due to ambiguity of lexical and semantic meanings of attribute names. The practical significance lies in the development of methods for organizing access to data in large subject areas, which together with the degree of efficiency of their processing serve as the foundation of the modern information industry and normalizes the vocabulary of subject area description and coordination of management tasks within a single approach.

Author Biographies

Ganna Pliekhova, Kharkov National Automobile and Highway University, 25, Yaroslava Mudrogo str., Kharkiv, 61002, Ukraine.

Assoc. Prof. Department of Computer Science and Applied Mathematics

Olena Alisejko, Kharkiv Institute of Radio Electronics, 14, Nauki str., Kharkiv, 61000, Ukraine.

Research part of the Kharkov Institute of Radio Electronics

Zoia Kochuieva, 3National Technical University “Kharkiv Polytechnic Institute”2, Kyrpychova str., 61002, Kharkiv, Ukraine.

Assoc. Prof. Department of Intelligent computer systems

References

Варламов О. О. Эволюционные базы данных и знаний для адаптивного синтеза интеллектуальных систем. Миварное информационное пространство. Радио и связь. 2002. Т. 286.

Гурин Н. И., Жук Я. А. Алгоритм подготовки текста обучающей информационной системы к семантическому аналізу. Труды БГТУ. Серия 3: Физико-математические науки и информатика. 2017. №9 (200). С. 105-109.

Bordawekar R., Shmueli O. Using Word Embedding to Enable Semantic Queries in Relational Databases. Proceedings of the 1st Workshop on Data Management for End-to-End Machine Learning. ACM, 2017. № 5. С. 1-4.

Li N., Bai L. Transforming fuzzy spatiotemporal data from relational databases to XML. IEEE Access. 2018. Т. 6. С. 4176-4185.

Tang P., Pitera J., Zubarev D., Chawla N. V. Materials Science Literature-Patent Relevance Search: A Heterogeneous Network Analysis Approach. Data Science and Advanced Analytics (DSAA), 2017 IEEE International Conference, 2017. С. 146-154.

Алісейко О. В. Організація баз даних : практикум. Харків : Фоп Коряк, 2019. 51 с.

Алісейко О.В., Бабенко В.О., Чала Л.Е. Орга-нізація та проектування баз даних в інфор-маційних системах: навчальний посібник. Харків : Компанія СМІТ. 2010. 164 c.

Алисейко Е. В. Internet-Технологии в бизнесе: учебное пособие. Харьков : Компания СМИТ, 2014. 340 с.

References

Varlamov, O. O. (2002). Evolyuczionnye bazy dannykh i znanij dlya adaptivnogo sinteza intellektualnykh sistem. Mivarnoe informa-czionnoe prostranstvo. [Evolutionary databases and knowledge for adaptive synthesis of intelligent systems]. Radio i svyaz. [in Russian].

Gurin, N. I., & Zhuk, Ya. A. (2017). Algoritm podgotovki teksta obuchayushhej informa-czionnoj sistemy k semanticheskomu analizu. [Algorithm for preparing the text of the learning information system for semantic analysis]. Trudy` BGTU. Seriya 3: Fiziko-matematicheskie nauki i informatika. 9, 105-109 [in Russian].

Bordawekar, R., & Shmueli, O. (2017, May). Using Word Embedding to Enable Semantic Queries in Relational Databases. Proceedings of the 1st Workshop on Data Management for End-toEnd Machine Learning. ACM. 5, 1-4.

Li, N., & Bai, L. (2018). Transforming fuzzy spatiotemporal data from relational databases to XML. IEEE Access, 6, 4176-4185 5. Tang, P., Pitera, J., Zubarev, D., & Chawla, N. V. (2017, October). Materials Science Literature-Patent Relevance Search: A Heterogeneous Network Analysis Approach. Data Science and Advanced Analytics (DSAA), 2017 IEEE International Conference, 146-154.

Tang, P., Pitera, J., Zubarev, D., & Chawla, N. V. (2017, October). Materials Science Literature-Patent Relevance Search: A Heterogeneous Network Analysis Approach. Data Science and Advanced Analytics (DSAA), 2017 IEEE International Conference, 146-154.

Aliseiko O.V. (2019). Organizacziya baz danikh: praktikum. [Organization of databases]. Kharkiv: Fop Koryak. [in Russian].

Aliseiko O.V., Babenko V.O., Chala L.E. (2010). Organizacziya ta proektuvannya baz danikh v i`nformaczi`ĭnikh sistemakh: navchal`niĭ posi`bnik. [Organization and design of databases in information systems]. Kharkiv : Kompani`ya SMI`T. [in Russian].

Aliseiko О. (2014). Internet-Tekhnologii v biznese [Internet-Technologies in business]: uchebnoe posobie. Khar`kov : Kompaniya SMIT [in Russian].

Published

2021-05-01

How to Cite

Pliekhova, G., Alisejko, O., & Kochuieva, Z. (2021). Application of semantic models and criteria equivalence of data to increase efficiency func-tioning of economic systems. Vehicle and Electronics. Innovative Technologies, (19), 41–46. https://doi.org/10.30977/VEIT.2021.19.0.41

Issue

Section

MODELING APPLIED TASKS IN AUTOMOBILE INDUSTRY AND TRANSPORT SYSTEMS