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| Issues | Sections | Authors | Keywords |
Article
| Issue: | 2025 №2 (90) |
| Section: | |
| UDK: | 330.341.1 |
| DOI: | https://doi.org/10.33271/ebdut/90.185 |
| Article language: | English |
| Pages: | 185-194 |
| Title: | Predictive monitoring of business processes within the framework of digital economy development |
| Author: | Mshvidobadze T. I., Gori State University |
| Annotation: | Methods. In this paper, we present an approach to analyze such event logs in order to predictively monitor business constraints during business process execution. At any point during an execution of a process, the user can define business constraints in the form of linear temporal logic rules. The framework defines the input data values that are more or less likely to meet each business constraint. The approach has been implemented in the ProM process mining toolset. Results. The results show that this model can provide competitive classification performance, create highly interpretable models, and effectively reduce data preparation efforts. The calculation of the information gain coefficient criteria is performed and shown in the algorithm using the appropriate equations and a recursive function. In this paper, we describe J48SS, a new decision tree inducer based on the C4.5 algorithm. The algorithm is experimentally validated on a real business speech analytics setting. J48SS is shown to effectively reduce the data preparation effort, and the use of binary splits shows that the tree grows fully. Future work could be devoted to investigating ensembles of J48 trees and applying the proposed algorithm to a corresponding database, where all types of supported attributes naturally arise. Also, a future research direction could be to extend the model to deal with temporal logic formulas. Such a formulation would allow the decision tree to take into account relationships between the values of different attributes, instead of looking at each of them individually. Novelty. This paper presents J48SS, a new decision tree learner that can blend static, sequential, and time-series data for classification purposes. The new algorithm is based on the popular C4.5 decision tree learner and relies on the concepts of frequent pattern extraction and timeseries formula generation. A framework for predictive business process monitoring is shown. Practical value. In this article, we propose implementation of the MapReduce C4.5 algorithm. Empirical results indicate that the implementation of the algorithm demonstrates both time efficiency and scalability. |
| Keywords: | Digital economy, Business process modeling, Process monitoring, C4.5 algorithm |
| File of the article: | EV20252_185-194.pdf |
| Literature: |
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Editor-in-Chief
Makurin A. A., Doctor of Economic Sciences, Professor, Department of International Relations and Audit, Dnipro University of Technology
Deputy Editors-in-Chief:
Buleev I. P., Doctor of Economic Sciences, Professor, Chief Researcher, Department of Enterprise Economics, Institute of Industrial Economics of the National Academy of Sciences of Ukraine, Ukraine
Vahonova O. H., Doctor of Economic Sciences, Professor, Head of the Department of Applied Economics, Entrepreneurship and Public Administration, Dnipro University of Technology
Chair of the Editorial Board
Bezuhla L. S., Doctor of Economic Sciences, Professor, Head of the Department of Tourism and Enterprise Economics, Dnipro University of Technology
Members of the Editorial Board:
- Andrii Andriiovych Makurin, Doctor of Economic Sciences, Professor, Professor at the Department of International Relations and Audit, Dnipro University of Technology, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0001-8093-736X - Oleksandra Hryhorivna Vahonova, Doctor of Economic Sciences, Professor, Head of the Department of Applied Economics, Entrepreneurship and Public Administration, Dnipro University of Technology, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0001-6553-7771 - Liudmyla Serhiivna Bezuhla, Doctor of Economic Sciences, Professor, Head of the Department of Tourism and Enterprise Economics, Dnipro University of Technology, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-6520-4325 - Maryna Illivna Ivanova, Doctor of Economic Sciences, Professor, Professor at the Department of Management, Dnipro University of Technology, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-1130-0186 - Oksana Vitaliivna Bashtannyk, Doctor of Sciences in Public Administration, Professor, Professor at the Department of History, Political Theory and Law, Dnipro University of Technology, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0003-4067-3261 - Olena Olehivna Akhmedova, Doctor of Sciences in Public Administration, Associate Professor, Professor at the Department of Tourism and Hotel and Restaurant Business, Kyiv National University of Technologies and Design, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0003-1573-7710 - Mykola Petrovych Horodyskyi, Candidate of Economic Sciences, Associate Professor, Zhytomyr Polytechnic State University, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-2093-5263 - Eleonora Yuriivna Tereshchenko, Candidate of Economic Sciences, Associate Professor, Associate Professor at the Department of Enterprise Economics and Finance, Kyiv National University of Trade and Economics, Ministry of Education and Science of Ukraine, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0003-2272-5224 - Valentyna Andriivna Pavlova, Doctor of Economic Sciences, Professor, Professor at the Department of Entrepreneurship, Alfred Nobel University, Dnipro, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-6762-8041 - Ivan Petrovych Buleev, Doctor of Economic Sciences, Professor, Chief Researcher, Department of Enterprise Economics, Institute of Industrial Economics of the National Academy of Sciences of Ukraine, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-7912-3649 - Olha Volodymyrivna Zakharova, Candidate of Economic Sciences, Associate Professor at the Department of International Economic Relations, Vasyl Stefanyk Carpathian National University, Ukraine, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-8718-0205 - Joanna Rosak-Szyrocka, PhD, Assistant Professor at Częstochowa University of Technology, Poland
https://wis.pcz.pl/wykladowcy---sprawozdawczosc/dr-joanna-rosak-szyrocka
https://orcid.org/0000-0002-5548-6787 - Jolanta Miko Nalivaike, Doctor of Social Sciences, specializing in Management, Vice-Dean of the Faculty of Business Management, Associate Professor at the Department of Management, Vilnius Gediminas Technical University (VILNIUS TECH), Lithuania, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0003-1009-4111 - Marat Kuralbekovich Kamysbayev, Doctor of Economic Sciences, Professor, Department of Management and Mathematical Economics, Kazakh National Research Technical University, Almaty, 050000, Kazakhstan, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-6952-6030 - Jan Skonieczny, PhD in Economics, Assistant Professor at the Department of Organization and Management, Wrocław University of Science and Technology, Poland, This email address is being protected from spambots. You need JavaScript enabled to view it.
https://orcid.org/0000-0002-1027-991X
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