13 citations · 20 across the 6 of their papers we have counts for
4 papers · 1 filter
Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas +2
Reducing cycle time is a recurrent concern in the field of business process management. Depending on the process, various interventions may be triggered to reduce the cycle time of…
A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Farbod Taymouri, Marcello La Rosa, Sarah M. Erfani
Event suffix and remaining time prediction are sequence to sequence learning tasks. They have wide applications in different areas such as economics, digital health, business proce…
Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs
Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas +2
This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given…
Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction
Farbod Taymouri, Marcello La Rosa, Sarah Erfani +2
Predictive process monitoring aims to predict future characteristics of an ongoing process case, such as case outcome or remaining timestamp. Recently, several predictive process m…