Alignments pinpoint trace deviations in a process model and quantify their severity. However, approaches based on trace alignments use crisp process models and recent probabilistic conformance checking approaches check the degree of conformance of an event log with respect to a stochastic process model instead of finding trace alignments. In this paper, for the first time, we provide a conformance checking approach based on trace alignments using stochastic Workflow nets. Conceptually, this requires to handle the two possibly contrasting forces of the cost of the alignment on the one hand and the likelihood of the model trace with respect to which the alignment is computed on the other.
Bergami, G., Maggi, F., Montali, M., Penaloza, R. (2021). A Tool for Computing Probabilistic Trace Alignments. In Lecture Notes in Business Information Processing (pp.118-126). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-79108-7_14].
A Tool for Computing Probabilistic Trace Alignments
Penaloza R.
2021
Abstract
Alignments pinpoint trace deviations in a process model and quantify their severity. However, approaches based on trace alignments use crisp process models and recent probabilistic conformance checking approaches check the degree of conformance of an event log with respect to a stochastic process model instead of finding trace alignments. In this paper, for the first time, we provide a conformance checking approach based on trace alignments using stochastic Workflow nets. Conceptually, this requires to handle the two possibly contrasting forces of the cost of the alignment on the one hand and the likelihood of the model trace with respect to which the alignment is computed on the other.File | Dimensione | Formato | |
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