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2018 | OriginalPaper | Buchkapitel

A Framework for Online Conformance Checking

verfasst von : Andrea Burattin, Josep Carmona

Erschienen in: Business Process Management Workshops

Verlag: Springer International Publishing

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Abstract

Conformance checking – a branch of process mining – focuses on establishing to what extent actual executions of a process are in line with the expected behavior of a reference model. Current conformance checking techniques only allow for a-posteriori analysis: the amount of (non-)conformant behavior is quantified after the completion of the process instance. In this paper we propose a framework for online conformance checking: not only do we quantify (non-)conformant behavior as the execution is running, we also restrict the computation to constant time complexity per event analyzed, thus enabling the online analysis of a stream of events. The framework is instantiated with ideas coming from the theory of regions, and state similarity. An implementation is available in ProM and promising results have been obtained.

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Vorheriges Kapitel Abduction for Generating Synthetic Traces

Nächstes Kapitel Recurrent Process Mining with Live Event Data

The coverability graph, actually, does not represent a good transition system for conformance purposes, as it allows for more behavior with respect to the original Petri nets. Therefore, in this paper, we assume that the given Petri net is bounded. This assumption is typically fulfilled in many real-world applications.

The OCTS of the system reported in Fig. 2b is available at https://andrea.burattin.net/public-files/online-conformance/octs.pdf.

The implementation is available in the StreamConformance package of ProM: https://svn.win.tue.nl/repos/prom/Packages/StreamConformance/.

The BPMN model is available at https://andrea.burattin.net/public-files/online-conformance/model.pdf.

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Titel: A Framework for Online Conformance Checking
verfasst von: Andrea Burattin
Josep Carmona
Verlag: Springer International Publishing
Buch: Business Process Management Workshops
Print ISBN: 978-3-319-74029-4

Electronic ISBN: 978-3-319-74030-0

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-74030-0_12

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