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Discovering and Navigating a Collection of Process Models Using Multiple Quality Dimensions Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Discovering Stochastic Petri Nets with Arbitrary Delay Distributions from Event Logs

Authors : Andreas Rogge-Solti, Wil M. P. van der Aalst, Mathias Weske

Published in: Business Process Management Workshops

Publisher: Springer International Publishing

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Abstract

Capturing the performance of a system or business process as accurately as possible is important, as models enriched with performance information provide valuable input for analysis, operational support, and prediction. Due to their computationally nice properties, memoryless models such as exponentially distributed stochastic Petri nets have earned much attention in research and industry. However, there are cases when the memoryless property is clearly not able to capture process behavior, e.g., when dealing with fixed time-outs.
We want to allow models to have generally distributed durations to be able to capture the behavior of the environment and resources as accurately as possible. For these more expressive process models, the execution policy has to be specified in more detail. In this paper, we present and evaluate process discovery algorithms for each of the execution policies. The introduced approach uses raw event execution data to discover various classes of stochastic Petri nets. The algorithms are based on the notion of alignments and have been implemented as a plug-in in the process mining framework ProM.

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previous chapter Discovering and Navigating a Collection of Process Models Using Multiple Quality Dimensions
next chapter Discovering Unbounded Synchronization Conditions in Artifact-Centric Process Models
Footnotes
1
See the StochasticPetriNet package of ProM (http://​www.​processmining.​org).
 
2
See package logspline in R. (http://​www.​r-project.​org/​).
 
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Metadata
Title
Discovering Stochastic Petri Nets with Arbitrary Delay Distributions from Event Logs
Authors
Andreas Rogge-Solti
Wil M. P. van der Aalst
Mathias Weske
Copyright Year
2014
Book
Business Process Management Workshops

Print ISBN: 978-3-319-06256-3

Electronic ISBN: 978-3-319-06257-0

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-06257-0_2

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