Open AccessDOI
Process mining and verification
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TLDR
This chapter introduces process model verification, and introduces techniques to check properties on a process model that check that every case that is started should be finished at some point, or that no case can result in a undesired state.Abstract:
ion of the process under consideration. Examples of properties that check whether that is the case are: that every case that is started should be finished at some point, or that no case can result in a undesired state. In this chapter, we introduce techniques to check such properties on a process model. More precisely, we introduce process model verification, as shown in Figure 5.1.read more
Citations
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Journal ArticleDOI
Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Journal ArticleDOI
Business process analysis in healthcare environments: A methodology based on process mining
Álvaro Rebuge,Diogo R. Ferreira +1 more
TL;DR: This work introduces a methodology for the application of process mining techniques that leads to the identification of regular behavior, process variants, and exceptional medical cases in a case study conducted at a hospital emergency service.
Book ChapterDOI
Process Discovery using Integer Linear Programming
TL;DR: In this paper, the authors present a process discovery algorithm using concepts taken from the language-based theory of regions, a well-known Petri net research area and identify a number of shortcomings of this theory from the process discovery perspective, and provide solutions based on integer linear programming.
Journal ArticleDOI
Production workflow: concepts and techniques
TL;DR: The authors may not be able to make you love reading, but production workflow concepts and techniques will lead you to love reading starting from now.
Book ChapterDOI
On the Role of Fitness, Precision, Generalization and Simplicity in Process Discovery
TL;DR: The quality of a process discovery algorithm is measured by quantifying to what extent the resulting model can reproduce the behavior in the log, i.e. replay fitness.
References
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Journal ArticleDOI
Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Journal ArticleDOI
Petri nets: Properties, analysis and applications
TL;DR: The author proceeds with introductory modeling examples, behavioral and structural properties, three methods of analysis, subclasses of Petri nets and their analysis, and one section is devoted to marked graphs, the concurrent system model most amenable to analysis.
Book
The Temporal Logic of Reactive and Concurrent Systems: Specification
Amir Pnueli,Zohar Manna +1 more
Book
Workflow Management: Models, Methods, and Systems
Wil vanderAalst,Kees M. van Hee +1 more
TL;DR: This book provides a basic overview of workflow terminology and organization, as well as detailed coverage of workflow modeling with Petri nets, to provide a comprehensive introduction to workflow management.
Business Process Execution Language for Web Services Version 1.1
TL;DR: The BPEL4WS specification defines an interoperable integration model that should facilitate the expansion of automated process integration in both the intracorporate and the business-to-business spaces.