Titlebook: Business Process Management Workshops; BPM 2023 Internation Jochen De Weerdt,Luise Pufahl Conference proceedings 2024 The Editor(s) (if app

Harass

Lecture Notes in Business Information Processinghttp://image.papertrans.cn/b/image/192353.jpg

INCUR

Joachim R. H?flich,Maren Hartmannsibilities may justify deviations. In these cases, we consider deviations as correct behaviors rather than errors. On the other hand, responsibilities can either be met or neglected in the execution trace. Thus, we prefer alignments where neglected responsibilities are minimized..The paper proposes

Estimable

Lumbar-Stenosis

https://doi.org/10.1007/978-3-322-92573-2e been improving the prediction accuracy for this suffix prediction task. Training such models with many parameters on large event logs requires expensive hardware and is often time consuming. Transfer learning addresses this issue by starting from a pre-trained model to be used as starting point fo

ALB

https://doi.org/10.1007/978-3-322-95690-3he development of foundation models for other domains and data modalities (e.g., images and code). In this paper, we argue that business process data has unique characteristics that warrant the creation of a new class of foundation models to handle tasks like activity prediction, process optimizatio

Clumsy

https://doi.org/10.1007/978-3-322-95690-3ains, such as the loan application process and the traffic fine process. However, care processes tend to be more dynamic and complex. For example, at any stage of a care process, a multitude of actions is possible. In this paper, we follow the reinforcement approach and train a Markov decision proce

新陳代謝

https://doi.org/10.1007/978-3-531-92218-8anding and data extraction domain. Several transformer based models such as LayoutLMv2 [.], LayoutLMv3 [.], and LiLT [.] have emerged achieving state of the art results. However, addition of even a single new class to the existing model requires (a) re-annotation of entire training dataset to includ

Ledger

Medienanalyse als Beobachtung und als Kritikg at cross-domain collaboration in production while exploiting semantically adequate and context-aware data at different levels of granularity. The . (IoT), in the context of production also referred to as . or the Industrial Internet of Things, provides a wide range of data assets. However, these a

Headstrong

Sinnstrukturen der Medienkommunikationse systems, thus allowing companies to analyze the data and gain valuable insights into user-product interactions. To analyze the underlying behavior recorded in data, process-mining techniques can be used. However, to apply process mining, the low-level measurements have to be transformed into an e

Inelasticity