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June 5, 2026
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Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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A Method to Improve Workflow Net Decomposition for Process Model Repair

Ch. 37. P. 411–423.
Semyon E. Tikhonov, Mitsyuk A. A.

Creating a process model (PM) is a convenient means to depict the behavior of a particular information system. However, user behavior is not static and tends to change over time. In order for them to sustain relevant, PMs have to be adjusted to ever-changing behavior. Sometimes the existing PM may be of high value (e.g. it is well-structured, or has been developed continuously by experts to later work with), which makes the approach to create a brand-new model using discovery algorithms less preferable. In this case, a different and better suitable approach to adjust PM to new behavior is to work with an existing model through repairing only such PM fragments that do not fit the actual behavior stated in sub-log. This article is to present a method for efficient decomposition of PMs for their future repair. It aims to improve the accuracy of model repair. Unlike the ones introduced earlier, this algorithm suggests finding the minimum spanning tree of undirected graph’s vertices subset. It helps to reduce the size of a fragment to be repaired in a model and enhances the quality of a repaired model according to various conformance metrics.

Language: English
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DOI
Text on another site
Keywords: сети Петриworkflow netsжурналы событийevent logsProcess model repairИсправление моделей процессов
Publication based on the results of:
Synthesis, recovery, conformance checking, and other methods for the analysis of process models and distributed information systems (2019)

In book

Analysis of Images, Social Networks and Texts. 8th International Conference AIST 2019
Springer, 2019.
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