Handling Concept Drift for Predictions in Business Process Mining

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Handling Concept Drift for Predictions in Business Process Mining

12 May 2020

Niklas Kühl

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Papers citing "Handling Concept Drift for Predictions in Business Process Mining"

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Title
StreamEnsemble: Predictive Queries over Spatiotemporal Streaming Data Anderson Chaves Eduardo S. Ogasawara P. Valduriez Fábio Porto AI4TS 39 0 0 30 Sep 2024
Machine learning in business process management: A systematic literature review Sven Weinzierl Sandra Zilker Sebastian Dunzer Martin Matzner 82 15 0 26 May 2024
Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages Silvia García-Méndez Francisco de Arriba-Pérez Ana Barros-Vila Francisco J. González Castaño 61 11 0 30 Mar 2024
Measuring the Stability of Process Outcome Predictions in Online Settings Suhwan Lee M. Comuzzi Xixi Lu H. Reijers 57 0 0 13 Oct 2023
Tailoring Machine Learning for Process Mining Paolo Ceravolo Sylvio Barbon Junior Ernesto Damiani Wil M.P. van der Aalst AI4TS 67 7 0 17 Jun 2023
Machine Learning for QoS Prediction in Vehicular Communication: Challenges and Solution Approaches Alexandros Palaios Christian L. Vielhaus D. Külzer Cara Watermann Rodrigo Hernangómez ... Martin Kasparick G. Fettweis F. Fitzek Hans D. Schotten Sławomir Stańczak 59 13 0 23 Feb 2023
ProcK: Machine Learning for Knowledge-Intensive Processes Tobias Jacobs Jingyi Yu J. Gastinger T. Sztyler 13 1 0 10 Sep 2021