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

疏遠(yuǎn)天際

Navigating Event Abstraction in Process Mining: A Comprehensive Analysis of Sub-problems, Data, and omplex process models. Event abstraction addresses this issue by transforming low-level event logs into abstracted event logs, enabling the derivation of business-level process models. However, practitioners often struggle to choose suitable event abstraction methods. This is primarily due to the la

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Timed Alignments with Mixed Movess at which each event is recorded. Time-aware process mining is a growing subfield of research, and as tools that seek to discover timing-related properties in processes develop, so does the need for conformance-checking techniques that can tackle time constraints and provide insightful quality meas

有其法作用

Joachim R. H?flich,Maren Hartmanna formal framework for responsibilities in a process model, including the definition of cost functions to determine optimal alignments. It also outlines a branch-and-bound algorithm for their computation.

Coronation

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Arresting

https://doi.org/10.1007/978-3-322-95690-3havior. We used the reinforcement learning algorithms Q-learning and SARSA to find optimal policies. Results showed that the policies derived from these algorithms are similar to the most frequent actions currently used but provide the staff members with a few more options in certain situations.

金桌活畫(huà)面

Regionale Publikumszeitschriften,e to address concurrency in IoT-aware processes. The approach is demonstrated in a scenario from smart manufacturing. The results show that PHILharmonicFlows offers a flexible and comprehensible solution for coordinating concurrent activities in IoT settings with constrained physical resources.

等級(jí)的上升

Accomplish

,Die Sucht nach der ?ffentlichkeit,tic model generation, there is still considerable scope for improvement. New technologies are continually being developed to support automatic model generation. Additionally, the increasing digitalization of processes and organizations generates vast amounts of data that can be harnessed for modeling.

Perennial長(zhǎng)期的

A Discussion on?Generalization in?Next-Activity Predictiondesigning robust evaluations requires a more profound conceptual engagement with the topic of next-activity prediction, and specifically with the notion of generalization to new data. To this end, we present various prediction scenarios that necessitate different types of generalization to guide future research.