Search Results for author: Beate Scheibel

Found 2 papers, 0 papers with code

An End-to-End Approach for Online Decision Mining and Decision Drift Analysis in Process-Aware Information Systems: Extended Version

no code implementations7 Mar 2023 Beate Scheibel, Stefanie Rinderle-Ma

Decision mining enables the discovery of decision rules from event logs or streams, and constitutes an important part of in-depth analysis and optimisation of business processes.

Comparing decision mining approaches with regard to the meaningfulness of their results

no code implementations15 Sep 2021 Beate Scheibel, Stefanie Rinderle-Ma

Decisions and the underlying rules are indispensable for driving process execution during runtime, i. e., for routing process instances at alternative branches based on the values of process data.

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