no code implementations • 27 Mar 2023 • Williams Rizzi, Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi
Recent papers have introduced a novel approach to explain why a Predictive Process Monitoring (PPM) model for outcome-oriented predictions provides wrong predictions.
no code implementations • 18 Oct 2022 • Williams Rizzi, Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi
Predictive Process Monitoring is a field of Process Mining that aims at predicting how an ongoing execution of a business process will develop in the future using past process executions recorded in event logs.
no code implementations • 15 Feb 2022 • Williams Rizzi, Marco Comuzzi, Chiara Di Francescomarino, Chiara Ghidini, Suhwan Lee, Fabrizio Maria Maggi, Alexander Nolte
The results of the user evaluation show that, although explanation plots are overall understandable and useful for decision making tasks for Business Process Management users -- with and without experience in Machine Learning -- differences exist in the comprehension and usage of different plots, as well as in the way users with different Machine Learning expertise understand and use them.
no code implementations • 8 Sep 2021 • Williams Rizzi, Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi
Existing well investigated Predictive Process Monitoring techniques typically construct a predictive model based on past process executions, and then use it to predict the future of new ongoing cases, without the possibility of updating it with new cases when they complete their execution.
no code implementations • 11 Apr 2018 • Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi, Williams Rizzi, Cosimo Damiano Persia
The results provide a first evidence of the potential of incremental learning strategies for predicting process monitoring in real environments, and of the impact of different case encoding strategies in this setting.