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Modeling and discovering cancelation behavior

Abstract

\u3cp\u3eThis paper presents a novel extension to the process tree model to support cancelation behavior, and proposes a novel process discovery technique to discover sound, fitting models with cancelation features. The proposed discovery technique relies on a generic error oracle function, and allows us to discover complex combinations of multiple, possibly nested cancelation regions based on observed behavior. An implementation of the proposed approach is available as a ProM plugin. Experimental results based on real-life event logs demonstrate the feasibility and usefulness of the approach.\u3c/p\u3

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    Last time updated on 06/12/2019

    This paper was published in Repository TU/e.

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