Decision Mining in a Broader Context: An Overview of the Current Landscape and Future Directions

  • Johannes De Smedt
  • Seppe K. L. M. vanden Broucke
  • Josue Obregon
  • Aekyung Kim
  • Jae-Yoon Jung
  • Jan Vanthienen
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 281)


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.


Decision mining Decision management DMN 



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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Johannes De Smedt
    • 1
  • Seppe K. L. M. vanden Broucke
    • 1
  • Josue Obregon
    • 2
  • Aekyung Kim
    • 2
  • Jae-Yoon Jung
    • 2
  • Jan Vanthienen
    • 1
  1. 1.Department of Decision Sciences and Information Management, Faculty of Economics and BusinessKU LeuvenLeuvenBelgium
  2. 2.Department of Industrial and Management Systems EngineeringKyung Hee UniversityYonginRepublic of Korea

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