Decision support for declarative artifact-centric process models

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Data-driven business processes involve knowledge workers that process information to take decisions. Such processes have been modelled successfully using artifact-centric process models. Artifacts represent business entities about which the knowledge workers collect and process information. Since information retrieval costs time and money, the key goal is to retrieve only the pieces of information that are needed to make a well-informed decision. To aid knowledge workers in achieving this goal, this paper realizes decision support for declarative artifact-centric process models by showing how declarative artifact-centric process models can be translated into Markov Decision Processes (MDP). The approach is illustrated with an example from the field of financial services.

Originele taal-2Engels
TitelBusiness Process Management Forum - BPM Forum 2019, Proceedings
RedacteurenThomas Hildebrandt, Boudewijn F. van Dongen, Maximilian Röglinger, Jan Mendling
Plaats van productieCham
UitgeverijSpringer
Pagina's36-52
Aantal pagina's17
ISBN van geprinte versie9783030266424
DOI's
StatusGepubliceerd - 2019
Evenement17th International Conference on Business Process Management, (BPM2019) - Vienna, Oostenrijk
Duur: 1 sep 20196 sep 2019
https://bpm2019.ai.wu.ac.at/

Publicatie series

NaamLecture Notes in Business Information Processing
Volume360
ISSN van geprinte versie1865-1348
ISSN van elektronische versie1865-1356

Congres

Congres17th International Conference on Business Process Management, (BPM2019)
Verkorte titelBPM2019
LandOostenrijk
StadVienna
Periode1/09/196/09/19
Internet adres

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Citeer dit

Voorberg, S., Eshuis, R., van Jaarsveld, W., & van Houtum, G. J. (2019). Decision support for declarative artifact-centric process models. In T. Hildebrandt, B. F. van Dongen, M. Röglinger, & J. Mendling (editors), Business Process Management Forum - BPM Forum 2019, Proceedings (blz. 36-52). (Lecture Notes in Business Information Processing; Vol. 360). Cham: Springer. https://doi.org/10.1007/978-3-030-26643-1_3