Massimo Guarascio
Massimo Guarascio
Researcher, Institute for high performance computing and networking (ICAR-CNR)
Verified email at icar.cnr.it - Homepage
Title
Cited by
Cited by
Year
Discovering context-aware models for predicting business process performances
F Folino, M Guarascio, L Pontieri
OTM Confederated International Conferences" On the Move to Meaningful …, 2012
1122012
Mining predictive process models out of low-level multidimensional logs
F Folino, M Guarascio, L Pontieri
International conference on advanced information systems engineering, 533-547, 2014
392014
A data-driven prediction framework for analyzing and monitoring business process performances
A Bevacqua, M Carnuccio, F Folino, M Guarascio, L Pontieri
International Conference on Enterprise Information Systems, 100-117, 2013
232013
Mining multi-variant process models from low-level logs
F Folino, M Guarascio, L Pontieri
International Conference on Business Information Systems, 165-177, 2015
202015
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
182019
High quality true-positive prediction for fiscal fraud detection
S Basta, F Fassetti, M Guarascio, G Manco, F Giannotti, D Pedreschi, ...
2009 IEEE International Conference on Data Mining Workshops, 7-12, 2009
182009
Discovering high-level performance models for ticket resolution processes
F Folino, M Guarascio, L Pontieri
OTM Confederated International Conferences" On the Move to Meaningful …, 2013
172013
A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators
F Francesco, M Guarascio, P Luigi
IEEE International Enterprise Distributed Object Computing Conference, EDOC …, 2015
16*2015
A cloud-based prediction framework for analyzing business process performances
E Cesario, F Folino, M Guarascio, L Pontieri
International Conference on Availability, Reliability, and Security, 63-80, 2016
142016
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
142016
Context-aware predictions on business processes: an ensemble-based solution
F Folino, M Guarascio, L Pontieri
International Workshop on New Frontiers in Mining Complex Patterns, 215-229, 2012
142012
A multi-view learning approach to the discovery of deviant process instances
A Cuzzocrea, F Folino, M Guarascio, L Pontieri
OTM Confederated International Conferences" On the Move to Meaningful …, 2015
132015
Rule learning with probabilistic smoothing
G Costa, M Guarascio, G Manco, R Ortale, E Ritacco
International Conference on Data Warehousing and Knowledge Discovery, 428-440, 2009
132009
A robust and versatile multi-view learning framework for the detection of deviant business process instances
A Cuzzocrea, F Folino, M Guarascio, L Pontieri
International Journal of Cooperative Information Systems 25 (04), 1740003, 2016
122016
A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances
A Bevacqua, M Carnuccio, F Folino, M Guarascio, L Pontieri
ICEIS (1), 56-65, 2013
122013
A Deep Learning Approach for Detecting Security Attacks on Blockchain
F Scicchitano, A Liguori, M Guarascio, E Ritacco, G Manco
72020
Deep learning
M Guarascio, G Manco, E Ritacco
Academic Press, 2019
72019
A descriptive clustering approach to the analysis of quantitative business-process deviances
F Folino, M Guarascio, L Pontieri
Proceedings of the Symposium on Applied Computing, 765-770, 2017
72017
On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-Structured Business Processes
F Folino, M Guarascio, L Pontieri
ICEIS (1) 1, 206-217, 2015
62015
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
52021
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