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Titlebook: Business Process Management; 21st International C Chiara Di Francescomarino,Andrea Burattin,Shazia S Conference proceedings 2023 The Editor

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發(fā)表于 2025-3-21 16:55:49 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Business Process Management
期刊簡稱21st International C
影響因子2023Chiara Di Francescomarino,Andrea Burattin,Shazia S
視頻videohttp://file.papertrans.cn/193/192332/192332.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Business Process Management; 21st International C Chiara Di Francescomarino,Andrea Burattin,Shazia S Conference proceedings 2023 The Editor
影響因子This book constitutes the refereed proceedings of the?21st International Conference on Business Process Management, BPM 2023, which took place in Utrecht, The Netherlands, in September 2023.?.The 27 papers included in this book were carefully reviewed and selected from 151 submissions. They were organized in three main research tracks: Foundations, engineering, and management.?.
Pindex Conference proceedings 2023
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書目名稱Business Process Management影響因子(影響力)




書目名稱Business Process Management影響因子(影響力)學(xué)科排名




書目名稱Business Process Management網(wǎng)絡(luò)公開度




書目名稱Business Process Management網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Business Process Management被引頻次




書目名稱Business Process Management被引頻次學(xué)科排名




書目名稱Business Process Management年度引用




書目名稱Business Process Management年度引用學(xué)科排名




書目名稱Business Process Management讀者反饋




書目名稱Business Process Management讀者反饋學(xué)科排名




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Event Abstraction for?Partial Order Patternsn framework based on partial order patterns. We extract the candidate pattern instances and abstract event data based on the pattern instances identified. Moreover, we instantiate the framework and optimize the implementation. The framework is evaluated with synthetic event data, and a case study ba
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POWL: Partially Ordered Workflow Languageure; i.e., POWL models can be combined into a new model either using a control-flow operator or as a partial order. We propose an initial approach to demonstrate the feasibility of using POWL models for process discovery, and we evaluate our approach based on real-life data.
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