Process Discovery

Process discovery is the automated extraction of process models from event logs, aiming to understand and improve real-world operational processes. Current research emphasizes improving model quality through multi-objective optimization algorithms (like those based on differential evolution or genetic algorithms), incorporating domain knowledge via large language models, and handling the complexities of unstructured data and diverse data types found in healthcare and other domains. These advancements enhance the accuracy, interpretability, and applicability of discovered models, leading to more effective process analysis and improvement across various sectors.