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• W615583150 abstract "AbstractService processes, for example in transportation, telecommunications or the health sector, are the backbone of today’s economies. Conceptual models of such service processes enable operational analysis that supports, e.g., resource provisioning or delay prediction. Automatic mining of such operational models becomes feasible in the presence of event-data traces. In this work, we target the mining of models that assume a resource-driven perspective and focus on queueing effects. We propose a solution for the discovery and validation problem of scheduled service processes - processes with a predefined schedule for the execution of activities. Our prime example for such processes are complex outpatient treatments that follow prior appointments. Given a process schedule and data recorded during process execution, we show how to discover Fork/Join networks, a specific class of queueing networks, and how to assess their operational validity. We evaluate our approach with a real-world dataset comprising clinical pathways of outpatient clinics, recorded by a real-time location system (RTLS). We demonstrate the value of the approach by identifying and explaining operational bottlenecks.KeywordsService TimeService ProcessService PolicySchedule ProcessProcess ExecutionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
• W615583150 created "2016-06-24" @default.
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• W615583150 date "2015-01-01" @default.
• W615583150 modified "2023-09-27" @default.
• W615583150 title "Discovery and Validation of Queueing Networks in Scheduled Processes" @default.
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• W615583150 doi "https://doi.org/10.1007/978-3-319-19069-3_26" @default.
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