We consider the scenario where the executions of different business processes are traced into a log, whose traces describe the process instances as sequences of low-level events (representing basic kinds of operations). In this context, we address the following problem: given a description of the processes’ behaviors in terms of high-level activities (instead of low-level events), and in the presence of uncertainty in the mapping between events and activities, find all the interpretations of each trace Φ, in terms of the process model that Φ conforms to and of the sequence of activities that may have triggered the events in Φ. We describe the probabilistic framework presented in [7] supporting the extraction of a compact representation of Φ’s interpretations, where each interpretation is associated with a probability score representing the probability of being the actual one.

On the interpretation of traces of low level events in business process logs Extended abstract

Fazzinga, Bettina;Flesca, Sergio;Furfaro, Filippo;Masciari, Elio;Pontieri, Luigi
2018-01-01

Abstract

We consider the scenario where the executions of different business processes are traced into a log, whose traces describe the process instances as sequences of low-level events (representing basic kinds of operations). In this context, we address the following problem: given a description of the processes’ behaviors in terms of high-level activities (instead of low-level events), and in the presence of uncertainty in the mapping between events and activities, find all the interpretations of each trace Φ, in terms of the process model that Φ conforms to and of the sequence of activities that may have triggered the events in Φ. We describe the probabilistic framework presented in [7] supporting the extraction of a compact representation of Φ’s interpretations, where each interpretation is associated with a probability score representing the probability of being the actual one.
2018
Business processes · Graph structure · Probabilistic conditioning; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/285539
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