Abstract
The term Decision Mining has been put forward in literature to cover numerous applications in a diverse set of contexts. In the business process management community, it typically reflects the way processes and data required for decision purposes in those processes are blended into one model during discovery. However, the upcoming field of decision modeling and management requires the term to be repositioned in order to obtain a better understanding of the interplay of processes and decisions. In this paper, the different approaches that are currently available are delineated and a case is made for a new type of decision mining: one that separates the control flow and decision perspective in a less stringent form compared to existing approaches.
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Acknowledgments
This work has been partially supported by funds from the the Flemish Fund for Science (grant FWO VS.010.14N) and from the National Research Foundation of Korea (NRF) grant (No. 2013R1A2A2A03014718).
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De Smedt, J., vanden Broucke, S.K.L.M., Obregon, J., Kim, A., Jung, JY., Vanthienen, J. (2017). Decision Mining in a Broader Context: An Overview of the Current Landscape and Future Directions. In: Dumas, M., Fantinato, M. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-319-58457-7_15
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DOI: https://doi.org/10.1007/978-3-319-58457-7_15
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