Abstract
The previous chapters presented a technique to detect precision issues between process models and logs. However, not all the detected precision problems have the same severity. A good diagnosis tool must evaluate and categorize them according to their importance. This chapter provides an assessment approach to measure the severity of the escaping arcs, quantifying their severity using four dimensions: weight, alternation, stability, and criticality. In later chapters, we will extend the precision detection to handle non-fitting scenarios.
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© 2016 Springer International Publishing AG
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Munoz-Gama, J. (2016). Assessing Severity. In: Conformance Checking and Diagnosis in Process Mining. Lecture Notes in Business Information Processing, vol 270. Springer, Cham. https://doi.org/10.1007/978-3-319-49451-7_8
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DOI: https://doi.org/10.1007/978-3-319-49451-7_8
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-49451-7
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