Summary: Handling Concept Drift in Process Mining
R.P. Jagadeesh Chandra Bose1,2
, Wil M.P. van der Aalst1
, Indre Zliobaite1
,
and Mykola Pechenizkiy1
1
Department of Mathematics and Computer Science, University of Technology,
Eindhoven, The Netherlands
2
Philips Healthcare, Veenpluis 5­6, Best, The Netherlands
{j.c.b.rantham.prabhakara,w.m.p.v.d.aalst,m.pechenizkiy}@tue.nl,
zliobaite@gmail.com
Abstract. Operational processes need to change to adapt to changing
circumstances, e.g., new legislation, extreme variations in supply and de-
mand, 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 pe-

Source: Aalst, W.M.P.van der - Wiskunde en Informatica, Technische Universiteit Eindhoven

Collections: Computer Technologies and Information Sciences