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Titlebook: Business Process Management Forum; BPM 2022 Forum, Müns Claudio Di Ciccio,Remco Dijkman,Stefanie Rinderle- Conference proceedings 2022 Spri

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樓主: LH941
41#
發(fā)表于 2025-3-28 15:24:42 | 只看該作者
42#
發(fā)表于 2025-3-28 22:03:01 | 只看該作者
Dealing with?Unexpected Runtime Outcomes Within Process Modelsesenting the tasks’ outcomes as data ranges. When a deviation is detected, the approach re-evaluates compliance of the model given the unexpected outcomes during the execution, and if necessary and possible it adapts the remainder of the model’s execution to preemptively avoid breaching the requirements.
43#
發(fā)表于 2025-3-29 00:41:57 | 只看該作者
Why Do Banks Find Business Process Compliance so?Challenging? An?Australian Perspectives, and the case for sustainable change remains elusive, locking banks into a fail-fix cycle that increases the underlying complexity. This paper proposes a conceptual framework that identifies and aggregates the challenges, and a circuit-breaker approach as an “off ramp” to the fail-fix cycle.
44#
發(fā)表于 2025-3-29 05:21:10 | 只看該作者
On the?Use of?the?Conformance and?Compliance Keywords During Verification of?Business Processeson paper, we aim to provide comprehensive definitions and a unified terminology throughout the BPM lifecycle. Moreover, we explore the consequences when these terms are used incorrectly. In doing so, we aim to improve adoption from research to practical applications by clarifying the relation betwee
45#
發(fā)表于 2025-3-29 11:14:44 | 只看該作者
46#
發(fā)表于 2025-3-29 12:36:34 | 只看該作者
47#
發(fā)表于 2025-3-29 18:19:17 | 只看該作者
48#
發(fā)表于 2025-3-29 21:24:20 | 只看該作者
49#
發(fā)表于 2025-3-29 23:55:29 | 只看該作者
Change Detection in?Dynamic Event Attributesess activities representing events with the same activity name. This can help to confirm expected behaviour of . event attributes, but also allows deriving novel insights by identifying unexpected changes. We applied the proposed technique on the MIMIC-IV real-world data set on hospitalizations in t
50#
發(fā)表于 2025-3-30 06:51:26 | 只看該作者
When to?Intervene? Prescriptive Process Monitoring Under Uncertainty and?Resource Constraintst filters and ranks ongoing cases based on prediction scores, prediction uncertainty, and causal effect of the intervention, and triggers interventions to maximize a gain function, considering the available resources. The proposal is evaluated using a real-life event log. The results show that the p
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