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Titlebook: Business Process Management Workshops; BPM 2009 Internation Stefanie Rinderle-Ma,Shazia Sadiq,Frank Leymann Conference proceedings 2010 Spr

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https://doi.org/10.1007/978-3-658-01940-2 can be used to discover better process models. This paper presents a new activity mining approach based on global trace segmentation. We also present an implementation of the approach, and we validate it using a real-life event log from ASML’s test process.
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https://doi.org/10.1007/978-3-658-15879-8ss is launched, the exact effect and affecting variables are not necessarily known. Our approach aims at categorizing possible environmental conditions and case properties into context categories which are meaningful for the process execution. This is achieved by a context learning framework, presented in the paper.
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Introduction to the Fourth Workshop on Business Process Design (BPD 2009)ogy means that the outcomes of such efforts are hard to predict. This is an unsatisfying situation for the academic and practical BPM community as process design plays an essential role in the overall business process lifecycle.
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Designing Generic Business Processes Based on SOA: An Approach and a Use Casemited to designing the Business process model and do not examine the challenges in propagating the same principles on to the implementation. Here, we propose an approach which covers the design & implementation to ensure reuse & flexibility while maintaining the other benefits of cost of ownership.
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Towards a Framework for Business Process Standardizationn a set of initial conjectures about successful process standardization. This exploratory research is a first step towards uncovering the characteristics of successful process standardization efforts.
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Autonomous Optimization of Business Processes their behavior in accordance to the current operating conditions for optimizing KPIs. The advantages of this method are discussed and statistically analyzed using a simulation based approach and the business process “new customer” found in banking.
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A Formal Model for Process Context Learningss is launched, the exact effect and affecting variables are not necessarily known. Our approach aims at categorizing possible environmental conditions and case properties into context categories which are meaningful for the process execution. This is achieved by a context learning framework, presented in the paper.
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