| An evolutionary multiobjective approach for community discovery in dynamic networks F Folino, C Pizzuti IEEE Transactions on Knowledge and Data Engineering 26 (8), 1838-1852, 2013 | 249 | 2013 |
| Discovering context-aware models for predicting business process performances F Folino, M Guarascio, L Pontieri On the Move to Meaningful Internet Systems: OTM 2012: Confederated …, 2012 | 132 | 2012 |
| Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction F Folino, G Greco, A Guzzo, L Pontieri Data & Knowledge Engineering 70 (12), 1005-1029, 2011 | 64 | 2011 |
| A multiobjective and evolutionary clustering method for dynamic networks F Folino, C Pizzuti 2010 international conference on advances in social networks analysis and …, 2010 | 59 | 2010 |
| Link prediction approaches for disease networks F Folino, C Pizzuti Information Technology in Bio-and Medical Informatics: Third International …, 2012 | 54 | 2012 |
| Mining predictive process models out of low-level multidimensional logs F Folino, M Guarascio, L Pontieri Advanced Information Systems Engineering: 26th International Conference …, 2014 | 47 | 2014 |
| A comorbidity network approach to predict disease risk F Folino, C Pizzuti, M Ventura Information Technology in Bio-and Medical Informatics, ITBAM 2010: First …, 2010 | 45 | 2010 |
| A comorbidity-based recommendation engine for disease prediction F Folino, C Pizzuti 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems …, 2010 | 36 | 2010 |
| Multiobjective evolutionary community detection for dynamic networks F Folino, C Pizzuti Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 32 | 2010 |
| On learning effective ensembles of deep neural networks for intrusion detection F Folino, G Folino, M Guarascio, FS Pisani, L Pontieri Information Fusion 72, 48-69, 2021 | 28 | 2021 |
| Boosting text segmentation via progressive classification E Cesario, F Folino, A Locane, G Manco, R Ortale Knowledge and Information Systems 15 (3), 285-320, 2008 | 28 | 2008 |
| A data-driven prediction framework for analyzing and monitoring business process performances A Bevacqua, M Carnuccio, F Folino, M Guarascio, L Pontieri Enterprise Information Systems: 15h International Conference, ICEIS 2013 …, 2014 | 25 | 2014 |
| Discovering expressive process models from noised log data F Folino, G Greco, A Guzzo, L Pontieri Proceedings of the 2009 international database engineering & applications …, 2009 | 25 | 2009 |
| Mining multi-variant process models from low-level logs F Folino, M Guarascio, L Pontieri Business Information Systems: 18th International Conference, BIS 2015 …, 2015 | 24 | 2015 |
| DynamicNet an effective and efficient algorithm for supporting community evolution detection in time-evolving information networks A Cuzzocrea, F Folino, C Pizzuti Proceedings of the 17th International Database Engineering & Applications …, 2013 | 22 | 2013 |
| Discovering High-Level Performance Models for Ticket Resolution Processes: (Short Paper) F Folino, M Guarascio, L Pontieri On the Move to Meaningful Internet Systems: OTM 2013 Conferences …, 2013 | 22 | 2013 |
| Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events A Cuzzocrea, F Folino, M Guarascio, L Pontieri Information Systems 81, 236-266, 2019 | 21 | 2019 |
| A multi-view multi-dimensional ensemble learning approach to mining business process deviances A Cuzzocrea, F Folino, M Guarascio, L Pontieri 2016 International Joint Conference on Neural Networks (IJCNN), 3809-3816, 2016 | 21 | 2016 |
| A cloud-based prediction framework for analyzing business process performances E Cesario, F Folino, M Guarascio, L Pontieri Availability, Reliability, and Security in Information Systems: IFIP WG 8.4 …, 2016 | 21 | 2016 |
| A prediction framework for proactively monitoring aggregate process-performance indicators F Folino, M Guarascio, L Pontieri 2015 IEEE 19th International Enterprise Distributed Object Computing …, 2015 | 20 | 2015 |
luigi pontieriResearcher, CNR, ICAREmail verificata su icar.cnr.it
