Titlebook: Business Process Management; 14th International C Marcello La Rosa,Peter Loos,Oscar Pastor Conference proceedings 2016 Springer Internation

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HOWL

Theodore M. Brown,Marcos Cueto,Elizabeth Feeitness, precision, generalization and simplicity. In this paper, we claim that stability could be considered as an important supplementary evaluation dimension for process discovery next to accuracy and comprehensibility, with ties to the generalization concept. As such, our core contribution is a n

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Theodore M. Brown,Marcos Cueto,Elizabeth Feeepresents the log from which it is learned. However, often the goal of discovery is not to represent the log, but the underlying system. This paper discusses the need to explicitly distinguish between a log and system perspective when interpreting the fitness and precision of a model. An empirical a

stressors

角斗士

https://doi.org/10.1057/9781137052889s, such as fitness or precision. Conversely, the methods proposed in this paper produce simplified models while preserving or even increasing fidelity metrics. The first problem addressed in the paper is the discovery of duplicate tasks. A new method is proposed that avoids overfitting by working on

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Scleroderma

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Preventive Aspects of Medical Care,tween the case in which a process execution recorded in event data “vacuously” satisfies a constraint, or satisfies the constraint in an “interesting way”. This fine-grained indicator is then used to decide whether a candidate constraint supported by the analyzed event log is indeed relevant or not.

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Afflict

The Greater Medical Profession,t of process models. The state of the art techniques for the computation of alignments rely on a full exploration of the combination of the model state space and the observed behavior (an event log), which hampers their applicability for large instances. This paper presents a fresh view to the align