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Evaluating Predictive Business Process Monitoring Approaches on Small Event Logs

Titelangaben

Käppel, Martin ; Jablonski, Stefan ; Schönig, Stefan:
Evaluating Predictive Business Process Monitoring Approaches on Small Event Logs.
In: Paiva, Ana C. R. ; Cavalli, Ana Rosa ; Martins, Paula Ventura ; Pérez-Castillo, Ricardo (Hrsg.): Quality of Information and Communications Technology : 14th International Conference, QUATIC 2021, Algarve, Portugal, September 8–11, 2021, Proceedings. - Cham : Springer , 2021 . - S. 167-182 . - (Communications in Computer and Information Science ; 1439 )
ISBN 978-3-030-85346-4

Volltext

Link zum Volltext (externe URL): Volltext

Abstract

Predictive business process monitoring is concerned with the prediction how a running process instance will unfold up to its completion at runtime. Most of the proposed approaches rely on a wide number of machine learning techniques. In the last years numerous studies revealed that these methods can be successfully applied for different prediction targets. However, these techniques require a qualitatively and quantitatively sufficient dataset. Unfortunately, there are many situations in business process management where only a quantitatively insufficient dataset is available. The problem of insufficient data in the context of BPM is still neglected. Hence, none of the comparative studies investigates the performance of predictive business process monitoring techniques in environments with small datasets. In this paper an evaluation framework for comparing existing approaches with regard to their suitability for small datasets is developed and exemplarily applied to state-of-the-art approaches in next activity prediction.

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Publikationsform: Aufsatz in einem Buch
Begutachteter Beitrag: Ja
Keywords: Process Mining; Predictive business process monitoring; Small Sample Learning; Process Prediction
Institutionen der Universität: Fakultäten > Fakultät für Mathematik, Physik und Informatik
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Angewandte Informatik IV
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Angewandte Informatik IV > Lehrstuhl Angewandte Informatik IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski
Fakultäten
Titel an der UBT entstanden: Ja
Themengebiete aus DDC: 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik
Eingestellt am: 30 Aug 2021 09:05
Letzte Änderung: 09 Aug 2023 10:41
URI: https://eref.uni-bayreuth.de/id/eprint/66873