A Review on Conformance Checking Technique for the Evaluation of Process Mining Algorithms

Information systems ease the collecting, processing, storing, and distributing informations, which in turn lead to decision-making and control in organizations. Information systems consist of information about key people, locations, and other important things in the organization. There is insufficient research on process mining, and the connection between data mining and model-driven process management. The goal of process mining is to discover, monitor, and improve processes by extracting knowledge from event logs. Conformance checking compares a process model with its event log. The inputs are event log and process model, while the output consists of diagnostic information, which shows differences and commonalities between the model and its log. The conformance checking technique is able to identify the similarities or differences between the process model and the event log. This research will introduce the conformance checking measures (fitness, precision, simplicity, and generalization) in order to improve the process model discovering from analytical aspects.