METHOD OF CONSTRUCTING AN ATTRIBUTE DESCRIPTION OF THE BUSINESS PROCESS "AS IS" IN THE PROCESS APPROACH TO ENTERPRISE MANAGEMENT

  • Serhii Chalyi Kharkiv National University of Radio Electronics
  • Ievgen Bogatov Kharkiv National University of Radio Electronics
Keywords: business processes, process management, process trace, event log, event attributes

Abstract

The problem of constructing an attribute description of a business process with the automated formation of process models “as is” using logs of information systems in which the tracks of individual processes are not identified is considered. It is shown that to solve this problem, it is advisable to distinguish the distinctive properties of individual business processes represented by the attributes of log events. A method for constructing an attribute description of a business process is proposed. The method is based on the comparison of combinations of attributes for intervals of events of a fixed length and the subsequent selection of subsets of attributes with the same values. The method includes the steps of forming the intervals of events, constructing combinations of attributes for specified intervals, as well as calculating and subsequently averaging the weights of combinations of attributes on these intervals. The result of the method is a weight-ordered set of event attributes and their values, which takes into account the attribute and temporal aspects of the business process. The method creates conditions for a more efficient transition from functional to process management based on splitting the log into processes using the resulting attribute description and subsequent prototyping of business process models “as is” by means of process mining.

Downloads

Download data is not yet available.

Author Biographies

Serhii Chalyi, Kharkiv National University of Radio Electronics

Department of Information Control Systems

Ievgen Bogatov, Kharkiv National University of Radio Electronics

Department of Information Control Systems

References

Dumas, M., La Rosa, M., Mendling, J., Reijers, H. A. (2013). Fundamentals of Business Process Management. Springer, 400. doi: https://doi.org/10.1007/978-3-642-33143-5

Van der Aalst, W. M. P. (2013). Business Process Management: A Comprehensive Survey. ISRN Software Engineering, 2013, 1–37. doi: https://doi.org/10.1155/2013/507984

Van der Aalst, W. (2016). Process Mining: Data Science in Action. Springer-Verlag, 467. doi: https://doi.org/10.1007/978-3-662-49851-4

Vom Brocke, J., Rosemann, M. (Eds.) (2015). Handbook on Business Process Management 1. Introduction, Methods, and Information Systems. Berlin: Springer-Verlag. doi: https://doi.org/10.1007/978-3-642-45100-3

Mannhardt, F., de Leoni, M., Reijers, H. A., van der Aalst, W. M. P., Toussaint, P. J. (2016). From Low-Level Events to Activities – A Pattern-Based Approach. Business Process Management, 125–141. doi: https://doi.org/10.1007/978-3-319-45348-4_8

Chalyi, S., Levykin, I., Petrychenko, A., Bogatov, I. (2018). Causality-based model checking in business process management tasks. 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT). doi: https://doi.org/10.1109/dessert.2018.8409176

Kalenkova, A. A., van der Aalst, W. M. P., Lomazova, I. A., Rubin, V. A. (2015). Process mining using BPMN: relating event logs and process models. Software & Systems Modeling, 16 (4), 1019–1048. doi: https://doi.org/10.1007/s10270-015-0502-0

Tax, N., Sidorova, N., Haakma, R., van der Aalst, W. M. P. (2016). Mining local process models. Journal of Innovation in Digital Ecosystems, 3 (2), 183–196. doi: https://doi.org/10.1016/j.jides.2016.11.001

Kalynychenko, O., Chalyi, S., Bodyanskiy, Y., Golian, V., Golian, N. (2013). Implementation of search mechanism for implicit dependences in process mining. 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS). doi: https://doi.org/10.1109/idaacs.2013.6662657

Van der Aalst W. M. P. (2013). A General Divide and Conquer Approach for Process Mining. Federated Conference on Computer Science and Information Systems (FedCSIS 2013). Available at: http://www.processmining.org/_media/blogs/pub2013/2-fedcis-wvdaalst-keynote.pdf

Van der Aalst, W. M. P. (2018). Process discovery from event data: Relating models and logs through abstractions. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8 (3), e1244. doi: https://doi.org/10.1002/widm.1244

Chalyi, S. F., Bogatov, E. O., Pribylnova, I. B. (2018). Techniques of reordering traces in the event logs in business process management tasks. Bulletin of National Technical University “KhPI”. Series: System Analysis, Control and Information Technologies, 21, 43–47. doi: https://doi.org/10.20998/2079-0023.2018.21.08


👁 419
⬇ 245
Published
2018-11-30
How to Cite
Chalyi, S., & Bogatov, I. (2018). METHOD OF CONSTRUCTING AN ATTRIBUTE DESCRIPTION OF THE BUSINESS PROCESS "AS IS" IN THE PROCESS APPROACH TO ENTERPRISE MANAGEMENT. EUREKA: Physics and Engineering, (6), 35-40. https://doi.org/10.21303/2461-4262.2018.00786
Section
Computer Science