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Erschienen in:
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2011 | OriginalPaper | Buchkapitel

5. Process Discovery: An Introduction

verfasst von : Wil M. P. van der Aalst

Erschienen in: Process Mining

Verlag: Springer Berlin Heidelberg

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Abstract

Process discovery is one of the most challenging process mining tasks. Based on an event log, a process model is constructed thus capturing the behavior seen in the log. This chapter introduces the topic using the rather naïve α-algorithm. This algorithm nicely illustrates some of the general ideas used by many process mining algorithms and helps to understand the notion of process discovery. Moreover, the α-algorithm serves as a stepping stone for discussing challenges related to process discovery.

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Vorheriges Kapitel Getting the Data
Nächstes Kapitel Advanced Process Discovery Techniques
Fußnoten
1
Nevertheless, the α-algorithm may construct a Petri net that is not a WF-net (see, for instance, Fig. 5.12). Later, we will discuss such problems in detail.
 
2
Note that the definition of noise may be a bit counter-intuitive. Sometimes the term “noise” is used to refer to incorrectly logged events, i.e., errors that occurred while recording the events. Such a definition is not very meaningful as no event log will explicitly reveal such errors. Hence, we consider “outliers” as noise. Moreover, we assume that such outliers correspond to exceptional behavior rather than logging errors.
 
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Metadaten
Titel
Process Discovery: An Introduction
verfasst von
Wil M. P. van der Aalst
Copyright-Jahr
2011
Verlag
Springer Berlin Heidelberg
Buch
Process Mining

Print ISBN: 978-3-642-19344-6

Electronic ISBN: 978-3-642-19345-3

Copyright-Jahr: 2011

DOI
https://doi.org/10.1007/978-3-642-19345-3_5