13 citations · 20 across the 3 of their papers we have counts for
8 papers
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…
Identifying candidate routines for Robotic Process Automation from unsegmented UI logs
V. Leno, A. Augusto, M. Dumas +3
Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions between users and software applications (a.k.a. routine…
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…
Automated Discovery of Data Transformations for Robotic Process Automation
Volodymyr Leno, Marlon Dumas, Marcello La Rosa +2
Robotic Process Automation (RPA) is a technology for automating repetitive routines consisting of sequences of user interactions with one or more applications. In order to fully ex…
Business Process Variant Analysis: Survey and Classification
Farbod Taymouri, Marcello La Rosa, Marlon Dumas +1
Process variant analysis aims at identifying and addressing the differences existing in a set of process executions enacted by the same process model. A process model can be execut…