Marcello La Rosa
Marcello La Rosa
Professor at University of Melbourne | Chief Executive Officer at Apromore
Verified email at - Homepage
Cited by
Cited by
Fundamentals of business process management
M Dumas, M La Rosa, J Mendling, HA Reijers
Springer 1, 2, 2013
Process mining manifesto
W Van Der Aalst, A Adriansyah, AKA De Medeiros, F Arcieri, T Baier, ...
Business Process Management Workshops: BPM 2011 International Workshops …, 2012
Blockchains for business process management-challenges and opportunities
J Mendling, I Weber, WVD Aalst, JV Brocke, C Cabanillas, F Daniel, ...
ACM Transactions on Management Information Systems (TMIS) 9 (1), 1-16, 2018
Predictive business process monitoring with LSTM neural networks
N Tax, I Verenich, M La Rosa, M Dumas
Advanced Information Systems Engineering: 29th International Conference …, 2017
Automated discovery of process models from event logs: Review and benchmark
A Augusto, R Conforti, M Dumas, M La Rosa, FM Maggi, A Marrella, ...
IEEE transactions on knowledge and data engineering 31 (4), 686-705, 2018
Business process management: Don’t forget to improve the process!
WMP Van Der Aalst, M La Rosa, FM Santoro
Business & Information Systems Engineering 58, 1-6, 2016
Outcome-oriented predictive process monitoring: Review and benchmark
I Teinemaa, M Dumas, ML Rosa, FM Maggi
ACM Transactions on Knowledge Discovery from Data (TKDD) 13 (2), 1-57, 2019
Configurable workflow models
F Gottschalk, WMP Van Der Aalst, MH Jansen-Vullers, M La Rosa
International Journal of Cooperative Information Systems 17 (02), 177-221, 2008
APROMORE: An advanced process model repository
M La Rosa, HA Reijers, WMP Van der Aalst, RM Dijkman, J Mendling, ...
Expert Systems with Applications, 2010
Configurable multi-perspective business process models
M La Rosa, M Dumas, AHM Ter Hofstede, J Mendling
Information Systems 36 (2), 313-340, 2011
Business process model merging: An approach to business process consolidation
M La Rosa, M Dumas, R Uba, R Dijkman
ACM Transactions on Software Engineering and Methodology (TOSEM) 22 (2), 1-42, 2013
Business process variability modeling: A survey
ML Rosa, WMPVD Aalst, M Dumas, FP Milani
ACM Computing Surveys (CSUR) 50 (1), 1-45, 2017
Managing large collections of business process models—Current techniques and challenges
R Dijkman, M La Rosa, HA Reijers
Computers in Industry 63 (2), 91-97, 2012
Introduction to business process management
M Dumas, M La Rosa, J Mendling, HA Reijers, M Dumas, M La Rosa, ...
Fundamentals of business process management, 1-33, 2018
Filtering out infrequent behavior from business process event logs
R Conforti, M La Rosa, AHM Ter Hofstede
IEEE Transactions on Knowledge and Data Engineering 29 (2), 300-314, 2016
Split miner: automated discovery of accurate and simple business process models from event logs
A Augusto, R Conforti, M Dumas, M La Rosa, A Polyvyanyy
Knowledge and Information Systems 59, 251-284, 2019
Questionnaire-based variability modeling for system configuration
M La Rosa, WMP van der Aalst, M Dumas, AHM Ter Hofstede
Software & Systems Modeling 8, 251-274, 2009
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
I Verenich, M Dumas, ML Rosa, FM Maggi, I Teinemaa
ACM Transactions on Intelligent Systems and Technology (TIST) 10 (4), 1-34, 2019
A recommendation system for predicting risks across multiple business process instances
R Conforti, M De Leoni, M La Rosa, WMP Van Der Aalst, ...
Decision Support Systems 69, 1-19, 2015
Managing process model complexity via concrete syntax modifications
M La Rosa, AHM Ter Hofstede, P Wohed, HA Reijers, J Mendling, ...
IEEE Transactions on Industrial Informatics 7 (2), 255-265, 2011
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