A Review of Process Discovery Methods and Conformance Checking Methods

With the ascent of data science, process mining has garnered increased attention. The objective of process mining is to extract valuable insights from event logs, facilitating the discovery, monitoring, and enhancement of real business processes. Process mining is primarily categorized into three research areas: process discovery, conformance checking, and process enhancement. The aim of process discovery is the automated extraction of process models from event logs. Conformance checking is primarily employed to assess the quality of the extracted models, thus evaluating the effectiveness of process discovery methods. Process enhancement involves expanding the model based on the outcomes of conformance checking. Conformance checking is primarily categorized into four quality dimensions: fitness, precision, generalization, and understandability. This paper predominantly examines process discovery and conformance checking methodologies.