Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20259

Title: Process Model Realism: Measuring Implicit Realism
Authors: Depaire, Benoit
Issue Date: 2015
Publisher: Springer International Publishing
Citation: Fournier, Fabiana; Mendling, Jan (Ed.). Business Process Management Workshops: BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers, p. 342-352
Series/Report: Lecture Notes in Business Information Processing
Series/Report no.: 202
Abstract: Determining the quality of a discovered process model is an important but non-trivial task. In this article, we focus on evaluating the realism level of a discovered process model, i.e. to what extent does the model contain the process behavior that is present in the true underlying process and nothing more. The IR Measure is proposed which represents the probability that a discovered model would have produced a log that is missing a certain amount of behavior observed in the discovered model. This measure expresses the strength of evidence that the discovered process model could be the true underlying model. Empirical results show that the Measure behaves as expected. The IR value drops when the discovered model contains unrealistic behavior. The IR value decreases as the amount of unrealistic behavior in the discovered model increases. The IR value increases as the amount of behavior in the underlying process increases, ceteris paribus.
URI: http://hdl.handle.net/1942/20259
DOI: 10.1007/978-3-319-15895-2_29
ISI #: 000364774100034
ISBN: 978-3-319-15894-5
ISSN: 1865-1348
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2016
Appears in Collections: Research publications

Files in This Item:

There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.