Process Mining
Process mining is a data-driven approach that uses event logs to analyze, visualize, and improve real-world business processes. Current research emphasizes enhancing the accuracy and fairness of predictive process monitoring, addressing challenges in handling uncertainty and large-scale data, and integrating advanced techniques like large language models (LLMs) and graph neural networks for improved process discovery, anomaly detection, and model interpretation. This field is significant for its ability to optimize operational efficiency, improve decision-making, and provide valuable insights across diverse domains, from healthcare to manufacturing.
Papers
An Explainable Decision Support System for Predictive Process Analytics
Riccardo Galanti, Massimiliano de Leoni, Merylin Monaro, Nicolò Navarin, Alan Marazzi, Brigida Di Stasi, Stéphanie Maldera
Clustering Object-Centric Event Logs
Anahita Farhang Ghahfarokhi, Fatemeh Akoochekian, Fareed Zandkarimi, Wil M. P. van der Aalst