Titlebook: Business Process Management; 17th International C Thomas Hildebrandt,Boudewijn F. van Dongen,Jan Men Conference proceedings 2019 Springer N

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Modeling and Reasoning over Declarative Data-Aware Processes with Object-Centric Behavioral Constrain focus on the control flow, lacking an explicit, conceptually well-founded integration with real data models, such as ER diagrams or UML class diagrams. To overcome this limitation, . (OCBC) models were recently proposed as a new notation that combines full-fledged data models with control-flow con

集合

Formal Modeling and SMT-Based Parameterized Verification of Data-Aware BPMN catalog and a read-write database called repository). The model trades off between expressiveness and the possibility of supporting parameterized verification of safety properties on top of it. Specifically, taking inspiration from the literature on verification of artifact systems, we study verifi

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ProcessExplorer: Intelligent Process Mining Guidancepetitive pressure in the market, organizations are particularly interested in optimizing their processes. Process mining enables the extraction of valuable knowledge from event logs, such as deviations, bottlenecks, and anomalies. Due to the increase of process complexity in flexible environments, v

隱語(yǔ)

Machine Learning-Based Framework for Log-Lifting in Business Process Mining Applicationsrocess mining techniques assume that there is a one-to-one mapping between process model activities and events recorded during process execution. Unfortunately, event logs and process model activities are defined at different levels of granularity. The challenges posed by this discrepancy can be add

錫箔紙

https://doi.org/10.1007/978-3-030-26619-6artificial intelligence; business process management; Business Process Management (BPM); databases; form

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