Provided by: Eindhoven University of Technology
Topic: Big Data
Date Added: May 2012
Process discovery algorithms typically aim at discovering process models from event logs that best describe the recorded behavior. Often, the quality of a process discovery algorithm is measured by quantifying to what extent the resulting model can reproduce the behavior in the log, i.e. replay fitness. At the same time, there are many other metrics that compare a model with recorded behavior in terms of the precision of the model and the extent to which the model generalizes the behavior in the log.