Decision support for declarative artifact-centric process models

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Abstract

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.

Original languageEnglish
Title of host publicationBusiness Process Management Forum - BPM Forum 2019, Proceedings
EditorsThomas Hildebrandt, Boudewijn F. van Dongen, Maximilian Röglinger, Jan Mendling
Place of PublicationCham
PublisherSpringer
Pages36-52
Number of pages17
ISBN (Print)9783030266424
DOIs
Publication statusPublished - 2019
Event17th International Conference on Business Process Management, (BPM2019) - Vienna, Austria
Duration: 1 Sep 20196 Sep 2019
https://bpm2019.ai.wu.ac.at/

Publication series

NameLecture Notes in Business Information Processing
Volume360
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Conference

Conference17th International Conference on Business Process Management, (BPM2019)
Abbreviated titleBPM2019
CountryAustria
CityVienna
Period1/09/196/09/19
Internet address

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Cite this

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 (Eds.), Business Process Management Forum - BPM Forum 2019, Proceedings (pp. 36-52). (Lecture Notes in Business Information Processing; Vol. 360). Cham: Springer. https://doi.org/10.1007/978-3-030-26643-1_3