Marcello La Rosa

Seven Paradoxes of Business Process Management in a Hyper-Connected World

D Beverungen, JCAM Buijs, J Becker, C Di Ciccio, WMP van der Aalst, C Bartelheimer, J vom Brocke, M Comuzzi, K Kraume, H Leopold, M Matzner, J Mendling, N Ogonek, T Post, M Resinas, K Revoredo, A del-Río-Ortega, M La Rosa, FM Santoro, A Solti, et al.

Journal article  |  2021  |  Business and Information Systems Engineering

AbstractBusiness Process Management is a boundary-spanning discipline that aligns operational capabilities and technology to desig..

Robotic Process Mining: Vision and Challenges

Volodymyr Leno, Artem Polyvyanyy, Marcello La Rosa, Marlon Dumas, Fabrizio Maggi

Journal article  |  2021  |  Business and Information Systems Engineering

Robotic process automation (RPA) is an emerging technology that allows organizations automating repetitive clerical tasks by execu..

Scalable alignment of process models and event logs: An approach based on automata and S-components

D Reißner, A Armas-Cervantes, R Conforti, M Dumas, D Fahland, M La Rosa

Report  |  2020  |  Information Systems

Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs

Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas, Marcello La Rosa, Artem Polyvyanyy

Conference Proceedings  |  2020  |  Proceedings of the 2020 2nd International Conference on Process Mining (ICPM)

This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of t..

Identifying candidate routines for Robotic Process Automation from unsegmented UI logs

Volodymyr Leno, Adriano Augusto, Marlon Dumas, Marcello La Rosa, Fabrizio Maria Maggi, Artem Polyvyanyy

Conference Proceedings  |  2020  |  Proceedings of the 2020 2nd International Conference on Process Mining (ICPM)

Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions betwe..

Business Process Variant Analysis Based on Mutual Fingerprints of Event Logs

F Taymouri, M La Rosa, J Carmona

Conference Proceedings  |  2020  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Comparing business process variants using event logs is a common use case in process mining. Existing techniques for process varia..

Robust drift characterization from event streams of business processes

A Ostovar, SJJ Leemans, ML Rosa

Report  |  2020  |  ACM Transactions on Knowledge Discovery from Data

Process workers may vary the normal execution of a business process to adjust to changes in their operational environment, e.g., c..

Detection and removal of infrequent behavior from event streams of business processes

SJ van Zelst, M Fani Sani, A Ostovar, R Conforti, M La Rosa

Journal article  |  2020  |  Information Systems

Process mining aims at gaining insights into business processes by analyzing the event data that is generated and recorded during ..

Automated discovery of declarative process models with correlated data conditions

V Leno, M Dumas, FM Maggi, M La Rosa, A Polyvyanyy

Journal article  |  2020  |  Information Systems

Automated process discovery techniques enable users to generate business process models from event logs extracted from enterprise ..

A Framework for Estimating Simplicity of Automatically Discovered Process Models Based on Structural and Behavioral Characteristics

Anna Kalenkova, Artem Polyvyanyy, Marcello La Rosa

Conference Proceedings  |  2020  |  Proceedings of the 18th International Conference on Business Process Management (BPM 2020)

A plethora of algorithms for automatically discovering process models from event logs has emerged. The discovered models are used ..