Bose R. P., J. C., van der Aalst, W. M.P., Zliobaite, I. and Pechenizkiy, M., 2011. Handling concept drift in process mining. In: 23rd International Conference on Advanced Information Systems Engineering, June 20-24 2011, London, UK, pp. 391-405.
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Operational processes need to change to adapt to changing circumstances, e.g., new legislation, extreme variations in supply and demand, seasonal effects, etc. While the topic of flexibility is well-researched in the BPM domain, contemporary process mining approaches assume the process to be in steady state. When discovering a process model from event logs, it is assumed that the process at the beginning of the recorded period is the same as the process at the end of the recorded period. Obviously, this is often not the case due to the phenomenon known as concept drift. While cases are being handled, the process itself may be changing. This paper presents an approach to analyze such second-order dynamics. The approach has been implemented in ProM and evaluated by analyzing an evolving process.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Generalities > Computer Science and Informatics > Artificial Intelligence|
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||Dr Indre Zliobaite LEFT|
|Deposited On:||12 Jul 2011 11:22|
|Last Modified:||07 Mar 2013 15:47|
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- Handling concept drift in process mining. (deposited 11 Apr 2011 16:35)
- Handling concept drift in process mining. (deposited 12 Jul 2011 11:22) [Currently Displayed]
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