Process Discovery Using Localized Events

Abstract

Process mining techniques aim to analyze and improve conformance and performance of processes using event data. Process discovery is the most prominent process-mining task: A process model is derived based on an event log. The process model should be able to capture causalities, choices, concurrency, and loops. Process discovery is very challenging because of trade-offs between fitness, simplicity, precision, and generalization. Note that event logs typically only hold example behavior and cannot be assumed to be complete (to avoid over fitting). Dozens of process discovery techniques have been proposed. These use a wide range of approaches, e.g., language- or state-based regions, genetic mi..