Process mining is a new method allowing the discovery of processes through databases. Using a log activity as input, process mining techniques allow to extract processes by selecting relevant pathways and displaying it using a graph. Such method may be used to extract processes from a wide range of systems: manufacturing systems, healthcare systems, network log activities, etc.
Scientific challenge related with process mining are related to: (i) data mining prior to process mining algorithm application (clustering of elements, cleaning of database); (ii) the improvement of models construction (increase the amount of information provided by the model while keeping it as small as possible); (iii) exploitation of such automatically built model using business process tools, discrete event simulation, etc. Specific usage of such technic may also be developed depending on the case study (for example heath data require specific treatment to better extract knowledge).
This special session aims at identifying crucial research progress in process mining. Scientists, researchers and engineers are invited to submit their current research related with process mining: recent developments in theory, computational studies, simulation, or combination of these.
Note: The topics include but are not limited to: Theoretical advances in process mining, Data mining for process mining, Applications of process mining, Case studies and lessons learned using process mining.