Process Discovery Using Domain Knowledge

This technical report discusses the application of domain knowledge in process discovery, emphasizing the relevance of event logs and process mining techniques. It outlines various process mining tasks such as discovery, alignment, replay, and enrichment. The report details examples of processes in different sectors, including banking, healthcare, and insurance, and highlights the significance of data extraction in these contexts. Additionally, it presents challenges in process discovery, including complexity and predictability, and introduces declarative constraints that can be applied to improve process models. The report also compares imperative and declarative models, emphasizing the importance of integrating process knowledge into mining frameworks. Furthermore, it discusses the limitations of existing inductive miners and proposes enhancements through the integration of large language models to facilitate better process model extraction. Overall, the report serves as a comprehensive guide for understanding and improving process discovery methodologies.