Investigating the Applicability of Cancellation Regions Discovery Algorithm for Synthesis of Process Models from Real Event Logs

Student: Zlobina Svetlana

Educational Programme: System and Software Engineering (Master)

Year of Graduation: 2021

Process mining is a field of data science which aims to improve real business processes by discovering and analyzing models of these processes using event logs. In the real life, many unexpected events may occur during the execution of a process, so that after the certain event several steps of the process are canceled. State-based region algorithm, which is widely used for discovering Petri nets from transition systems, gives models with overcomplicated and poorly readable structure in case of cancellations. Recently a novel method to discover cancellation regions based on transition system decomposition was proposed. In this work we implement the newly suggested method as a ProM and investigate its applicability for process models discovery from real event logs.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses