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Titlebook: Business Process Management Forum; BPM Forum 2018, Sydn Mathias Weske,Marco Montali,Jan vom Brocke Conference proceedings 2018 Springer Nat

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31#
發(fā)表于 2025-3-26 23:30:05 | 只看該作者
Lecture Notes in Business Information Processinghttp://image.papertrans.cn/b/image/192347.jpg
32#
發(fā)表于 2025-3-27 02:19:17 | 只看該作者
Business Process Management Forum978-3-319-98651-7Series ISSN 1865-1348 Series E-ISSN 1865-1356
33#
發(fā)表于 2025-3-27 08:24:52 | 只看該作者
Process Mining Crimes – A Threat to the Validity of Process Discovery Evaluationsf every publication. In this paper, we present a set of 20 scientifically supported “process mining crimes”, unintentional mistakes that threaten the validity of process discovery evaluations. To determine their prevalence even in high-quality publications, we perform a meta-evaluation of 21 process
34#
發(fā)表于 2025-3-27 12:20:53 | 只看該作者
A Logical Formalization of Time-Critical Processes with Resourcesnderstanding at design time the interactions of concurrent activities along the time line can become quite cumbersome, even for expert designers. In this paper, we consider processes that are composed of activities having a constrained duration and a bounded number of allocated resources, and we rel
35#
發(fā)表于 2025-3-27 16:35:44 | 只看該作者
36#
發(fā)表于 2025-3-27 19:06:12 | 只看該作者
Business Process Activity Relationships: Is There Anything Beyond Arrows?ts to be represented. Despite the variety of approaches, graphical symbols, and (in)formal interpretations associated to the different languages, a fundamental component of every business process modelling language is the representation of the way activities are related by means of control arcs and
37#
發(fā)表于 2025-3-28 01:46:38 | 只看該作者
38#
發(fā)表于 2025-3-28 02:52:46 | 只看該作者
Alarm-Based Prescriptive Process Monitoring of ongoing cases thereof. Existing techniques in this field are able to predict, at each step of a case, the likelihood that the case will end up in an undesired outcome. These techniques, however, do not take into account what process workers may do with the generated predictions in order to decre
39#
發(fā)表于 2025-3-28 08:29:34 | 只看該作者
iProcess: Enabling IoT Platforms in Data-Driven Knowledge-Intensive Processes world, has the potential to transform many industries. This includes harnessing real-time intelligence to improve risk-based decision making and supporting adaptive processes from core to edge. For example, modern police investigation processes are often extremely complex, data-driven and knowledge
40#
發(fā)表于 2025-3-28 12:46:06 | 只看該作者
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