4 papers
Exploring LLM Features in Predictive Process Monitoring for Small-Scale Event-Logs
Alessandro Padella, Massimiliano de Leoni, Marlon Dumas
Predictive Process Monitoring is a branch of process mining that aims to predict the outcome of an ongoing process. Recently, it leveraged machine-and-deep learning architectures.…
An Experimental Comparison of Alternative Techniques for Event-Log Augmentation
Alessandro Padella, Francesco Vinci, Massimiliano de Leoni
Process mining analyzes and improves processes by examining transactional data stored in event logs, which record sequences of events with timestamps. However, the effectiveness of…
Leveraging Data Augmentation and Siamese Learning for Predictive Process Monitoring
Sjoerd van Straten, Alessandro Padella, Marwan Hassani
Predictive Process Monitoring (PPM) enables forecasting future events or outcomes of ongoing business process instances based on event logs. However, deep learning PPM approaches a…
Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)
Massimiliano de Leoni, Alessandro Padella
Predictive business process analytics has become important for organizations, offering real-time operational support for their processes. However, these algorithms often perform un…