Process Mining
Overview
Process mining studies how recorded activities reveal the actual paths people and systems take through workflows, helping organizations find bottlenecks, check rules, and anticipate outcomes. Discovery methods build process models such as Petri nets from event logs, while conformance checking compares observed behavior with models or guidelines. Predictive approaches use sequence models, graphs, and probabilistic methods to forecast next activities, durations, or risks; newer work also uses object-centric data and language models to extract or explain processes. A central challenge is balancing accurate, useful models with incomplete or noisy logs, especially when case-based representations hide concurrency and rare but important behavior.
Latest papers
45 papers3 papers in the last four weeks, down 75% on the four weeks before. 0.0% of all new papers.