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Published in:
2013 | OriginalPaper | Chapter
Process Discovery Using Prior Knowledge
Authors : Aubrey J. Rembert, Amos Omokpo, Pietro Mazzoleni, Richard T. Goodwin
Published in: Service-Oriented Computing
Publisher: Springer Berlin Heidelberg
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In this paper, we describe a process discovery algorithm that leverages prior knowledge and process execution data to learn a control-flow model. Most process discovery algorithms are not able to exploit prior knowledge supplied by a domain expert. Our algorithm incorporates prior knowledge using ideas from Bayesian statistics. We demonstrate that our algorithm is able to recover a control-flow model in the presence of noisy process execution data, and uncertain prior knowledge.