Titlebook: Business Process Management Workshops; BPM 2022 Internation Cristina Cabanillas,Niels Frederik Garmann-Johnsen Conference proceedings 2023

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https://doi.org/10.1007/978-3-658-25224-3oblem of label ambiguity in process prediction and quantify the occurrence of ambiguous ground truth labels in common benchmark datasets. Finally, we discuss implications and present ideas that aim to initiate a discussion on how to deal with label ambiguity in process prediction.

正面

Dendritic-Cells

TEN

Anthology

Nausea

Automated Intelligent Assistance with?Explainable Decision Models in?Knowledge-Intensive Processesplanation facilities of an automated DMN intelligent assistant. The first findings from this ongoing research provide insights into how organizations could easily provide stakeholders with explainable decisions in processes.

引導(dǎo)

The Label Ambiguity Problem in?Process Predictionoblem of label ambiguity in process prediction and quantify the occurrence of ambiguous ground truth labels in common benchmark datasets. Finally, we discuss implications and present ideas that aim to initiate a discussion on how to deal with label ambiguity in process prediction.

新手

Situation-Aware eXplainability for?Business Processes Enabled by?Complex Eventsy. Specifically, we demonstrate our approach using a dataset populated for an illustrative process example, replaying its trace log against the PROTON CEP engine and feeding the result as an input for the SHAP explainer.

aristocracy

Assessing the?Suitability of?Traditional Event Log Standards for?IoT-Enhanced Event Logsh present important limitations to storing IoT-enhanced event logs. Based on this analysis, we conclude that a comprehensive data model is required to develop more advanced IoT-enhanced PM techniques.