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2015 | OriginalPaper | Buchkapitel

Bidimensional Process Discovery for Mining BPMN Models

verfasst von : Jochen De Weerdt, Seppe K. L. M. vanden Broucke, Filip Caron

Erschienen in: Business Process Management Workshops

Verlag: Springer International Publishing

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Abstract

This paper presents “BPMN Miner”, a process discovery technique that uses BPMN as the representational language for the discovery result. The proposed approach is novel in the sense that it is able to represent control-flow with BPMN constructs, but also because it augments the control-flow perspective with an organizational dimension by discovering swimlanes that represent organizational roles in the business process. Additional advantages of the proposed mining approach can be summarized as follows: it provides intuitive and easy-to-use abstraction/specification functionality which makes it applicable to event logs with various complexity levels, it provides instant feedback about the conformance between the input log and the resulting model based on a dedicated fitness metric, it is robust to noise, and it can easily integrate with modeling and other BPM tools with exporting functionality through the XPDL-format. In this way, BPMN Miner will take process mining one step closer to the status of indispensable for business process reengineering as discovered models are immediately available in the preferred language of a majority of practitioners, educators and researchers.

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Fußnoten
1
In analogy with the WEKA toolkit for data mining, ProM is an extensible framework that supports a wide variety of process mining techniques in the form of plug-ins. See: http://​www.​processmining.​org.
 
2
We assume here that the input and output sets are ordered. \(O(a)^{k}\) thus returns the \(j\)th subset of \(O(a)\).
 
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Metadaten
Titel
Bidimensional Process Discovery for Mining BPMN Models
verfasst von
Jochen De Weerdt
Seppe K. L. M. vanden Broucke
Filip Caron
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-15895-2_45