intrinsic
发表于 2025-3-21 16:46:03
书目名称Business Process Management Workshops影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0192353<br><br> <br><br>书目名称Business Process Management Workshops读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0192353<br><br> <br><br>
leniency
发表于 2025-3-21 22:03:24
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climax
发表于 2025-3-22 00:36:42
Medienanalyse als Beobachtung und als Kritik view their operational processes from any perspective using a single source of truth. However, OCED is not suitable for low-level machine data that contain a mixture of continuous measurements (e.g., time series data describing position, temperature, force, speed, etc.) and discrete events. Therefo
Herpetologist
发表于 2025-3-22 06:28:53
1865-1348Processing for Business Process Management (NLP4BPM 2023).• 1st International Workshop on Object-Centric Processes from A to Z (OBJECTS 2023).• 3rd Internation978-3-031-50973-5978-3-031-50974-2Series ISSN 1865-1348 Series E-ISSN 1865-1356
Implicit
发表于 2025-3-22 11:14:23
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现晕光
发表于 2025-3-22 14:42:21
An Experiment on Transfer Learning for Suffix Prediction on Event Logs two sequential deep learning architectures (GPT and LSTM). Base models are trained on two public event logs and used as starting point for transfer learning on eight event logs from different domains. The experiments show that even with half of the available training budget and without using very l
高度赞扬
发表于 2025-3-22 19:41:37
ProtoNER: Few Shot Incremental Learning for Named Entity Recognition Using Prototypical Networkse need to retain original training dataset for longer duration as well as data re-annotation which is very time consuming task, (2) No intermediate synthetic data generation which tends to add noise and results in model’s performance degradation, and (3) Hybrid loss function which allows model to re
持久
发表于 2025-3-22 21:47:53
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新奇
发表于 2025-3-23 03:07:56
https://doi.org/10.1007/978-3-031-50974-2business process management; business process modeling; business process monitoring; business process o
BLA
发表于 2025-3-23 08:48:36
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