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Francesco Folino
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2020 – today
- 2024
- [j16]Francesco Folino, Gianluigi Folino, Francesco Sergio Pisani, Luigi Pontieri, Pietro Sabatino:
Efficiently approaching vertical federated learning by combining data reduction and conditional computation techniques. J. Big Data 11(1): 77 (2024) - [j15]Francesco Folino, Gianluigi Folino, Massimo Guarascio
, Luigi Pontieri:
Data- & compute-efficient deviance mining via active learning and fast ensembles. J. Intell. Inf. Syst. 62(4): 995-1019 (2024) - [j14]Francesco Folino, Gianluigi Folino, Massimo Guarascio
Towards Data- and Compute-Efficient Fake-News Detection: An Approach Combining Active Learning and Pre-Trained Language Models. SN Comput. Sci. 5(5): 470 (2024) - [c54]Riccardo Graziosi, Massimiliano Ronzani, Andrei Buliga, Chiara Di Francescomarino, Francesco Folino, Chiara Ghidini, Francesca Meneghello, Luigi Pontieri:
Generating the Traces You Need: A Conditional Generative Model for Process Mining Data. ICPM 2024: 25-32 - [c53]Francesco Folino, Gianluigi Folino, Francesco Sergio Pisani, Pietro Sabatino, Luigi Pontieri:
A Scalable Vertical Federated Learning Framework for Analytics in the Cybersecurity Domain. PDP 2024: 245-252 - [i1]Francesco Folino, Luigi Pontieri, Pietro Sabatino:
Discussion: Effective and Interpretable Outcome Prediction by Training Sparse Mixtures of Linear Experts. CoRR abs/2407.13526 (2024) - 2023
- [c52]Francesco Folino
Sparse Mixtures of Shallow Linear Experts for Interpretable and Fast Outcome Prediction. ICPM Workshops 2023: 141-152 - 2022
- [j13]Francesco Folino
Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs. Bus. Inf. Syst. Eng. 64(6): 729-749 (2022) - [c51]Nunziato Cassavia, Francesco Folino, Massimo Guarascio
Detecting DoS and DDoS Attacks through Sparse U-Net-like Autoencoders. ICTAI 2022: 1342-1346 - [c50]Francesco Folino
Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery. ISMIS 2022: 346-356 - 2021
- [j12]Francesco Folino
On learning effective ensembles of deep neural networks for intrusion detection. Inf. Fusion 72: 48-69 (2021) - [j11]Francesco Folino
AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion. J. Data Semant. 10(1-2): 77-106 (2021) - [j10]Francesco Folino
Correction to: AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion. J. Data Semant. 10(3-4): 409 (2021) - 2020
- [j9]Bettina Fazzinga
An ensemble-based approach to the security-oriented classification of low-level log traces. Expert Syst. Appl. 153: 113386 (2020) - [c49]Francesco Folino, Gianluigi Folino, Luigi Pontieri
A p2p environment to validate ensemble-based approaches in the cybersecurity domain. PDP 2020: 344-351 - [c48]Francesco Folino, Gianluigi Folino, Massimo Guarascio
A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances. PKDD/ECML Workshops 2020: 249-262 - [c47]Francesco Folino, Massimo Guarascio
Exploiting Temporal Convolution for Activity Prediction in Process Analytics. PKDD/ECML Workshops 2020: 263-275
2010 – 2019
- 2019
- [j8]Alfredo Cuzzocrea
Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events. Inf. Syst. 81: 236-266 (2019) - [c46]Francesco Folino, Luigi Pontieri
Pushing More AI Capabilities into Process Mining to Better Deal with Low-Quality Logs. Business Process Management Workshops 2019: 5-11 - [c45]Francesco Folino, Gianluigi Folino, Massimo Guarascio
Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data. ICTAI 2019: 1396-1400 - [r1]Francesco Folino, Luigi Pontieri:
Business Process Deviance Mining. Encyclopedia of Big Data Technologies 2019 - 2018
- [j7]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
Deviance-Aware Discovery of High-Quality Process Models. Int. J. Artif. Intell. Tools 27(7): 1860009:1-1860009:27 (2018) - [c44]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events. IDEAS 2018: 165-174 - [c43]Francesco Folino, Gianluigi Folino, Luigi Pontieri
An Ensemble-Based P2P Framework for the Detection of Deviant Business Process Instances. HPCS 2018: 122-129 - [c42]Bettina Fazzinga
Combining Model- and Example-Driven Classification to Detect Security Breaches in Activity-Unaware Logs. OTM Conferences (2) 2018: 173-190 - 2017
- [c41]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning. ICEIS (Revised Selected Papers) 2017: 96-124 - [c40]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
Extensions, Analysis and Experimental Assessment of a Probabilistic Ensemble-learning Framework for Detecting Deviances in Business Process Instances. ICEIS (1) 2017: 162-173 - [c39]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
Deviance-Aware Discovery of High Quality Process Models. ICTAI 2017: 724-731 - [c38]Francesco Folino, Gianluigi Folino
A Peer-to-Peer Architecture for Detecting Attacks from Network Traffic and Log Data. HPCS 2017: 769-776 - [c37]Francesco Folino, Massimo Guarascio
A descriptive clustering approach to the analysis of quantitative business-process deviances. SAC 2017: 765-770 - 2016
- [j6]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances. Int. J. Cooperative Inf. Syst. 25(4): 1740003:1-1740003:56 (2016) - [c36]Eugenio Cesario
A Cloud-Based Prediction Framework for Analyzing Business Process Performances. CD-ARES 2016: 63-80 - [c35]Alfredo Cuzzocrea, Francesco Folino, Massimo Guarascio
A multi-view multi-dimensional ensemble learning approach to mining business process deviances. IJCNN 2016: 3809-3816 - 2015
- [j5]Francesco Folino
A recommendation engine for disease prediction. Inf. Syst. E Bus. Manag. 13(4): 609-628 (2015) - [c34]Francesco Folino
Mining Multi-variant Process Models from Low-Level Logs. BIS 2015: 165-177 - [c33]Francesco Folino, Massimo Guarascio
A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators. EDOC 2015: 128-133 - [c32]Francesco Folino, Massimo Guarascio
On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes. ICEIS (1) 2015: 206-217 - [c31]Alfredo Cuzzocrea, Francesco Folino
A Multi-view Learning Approach to the Discovery of Deviant Process Instances. OTM Conferences 2015: 146-165 - 2014
- [j4]Francesco Folino
An Evolutionary Multiobjective Approach for Community Discovery in Dynamic Networks. IEEE Trans. Knowl. Data Eng. 26(8): 1838-1852 (2014) - [c30]Francesco Folino
Mining Predictive Process Models out of Low-level Multidimensional Logs. CAiSE 2014: 533-547 - [c29]Francesco Folino, Massimo Guarascio
A Framework for the Discovery of Predictive Fix-time Models. ICEIS (1) 2014: 99-108 - [c28]Francesco Folino
An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models. ICEIS (Revised Selected Papers) 2014: 108-128 - 2013
- [j3]Francesco Folino
Methods and techniques for discovering taxonomies of behavioral process models. WIREs Data Mining Knowl. Discov. 3(3): 170-189 (2013) - [c27]Alfredo Cuzzocrea
Community evolution detection in time-evolving information networks. EDBT/ICDT Workshops 2013: 93-96 - [c26]Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio
A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances. ICEIS (1) 2013: 56-65 - [c25]Antonio Bevacqua, Marco Carnuccio, Francesco Folino
A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances. ICEIS 2013: 100-117 - [c24]Alfredo Cuzzocrea
DynamicNet: an effective and efficient algorithm for supporting community evolution detection in time-evolving information networks. IDEAS 2013: 148-153 - [c23]Francesco Folino
Discovering High-Level Performance Models for Ticket Resolution Processes. OTM Conferences 2013: 275-282 - [c22]Antonio Bevacqua, Marco Carnuccio, Francesco Folino, Massimo Guarascio, Luigi Pontieri:
Adaptive Trace Abstraction Approach for Predicting Business Process Performances. SEBD 2013: 437-444 - 2012
- [c21]Francesco Folino
Link Prediction Approaches for Disease Networks. ITBAM 2012: 99-108 - [c20]Francesco Folino
Discovering Context-Aware Models for Predicting Business Process Performances. OTM Conferences (1) 2012: 287-304 - [c19]Francesco Folino
Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. NFMCP 2012: 215-229 - 2011
- [j2]Francesco Folino
Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction. Data Knowl. Eng. 70(12): 1005-1029 (2011) - [c18]Francesco Folino
Combining Markov Models and Association Analysis for Disease Prediction. ITBAM 2011: 39-52 - 2010
- [c17]Francesco Folino
A Multiobjective and Evolutionary Clustering Method for Dynamic Networks. ASONAM 2010: 256-263 - [c16]Francesco Folino
A comorbidity-based recommendation engine for disease prediction. CBMS 2010: 6-12 - [c15]Francesco Folino
Multiobjective evolutionary community detection for dynamic networks. GECCO 2010: 535-536 - [c14]Alfredo Cuzzocrea, Francesco Folino, Luigi Pontieri:
Effective Analysis of Flexible Collaboration Processes by Way of Abstraction and Mining Techniques. ICEIS (2) 2010: 157-166 - [c13]Francesco Folino
Scalable parallel co-clustering over multiple heterogeneous data types. HPCS 2010: 529-535 - [c12]Francesco Folino
A Comorbidity Network Approach to Predict Disease Risk. ITBAM 2010: 102-109
2000 – 2009
- 2009
- [c11]Francesco Folino
Discovering expressive process models from noised log data. IDEAS 2009: 162-172 - 2008
- [j1]Eugenio Cesario
Boosting text segmentation via progressive classification. Knowl. Inf. Syst. 15(3): 285-320 (2008) - [c10]Stefano Basta, Francesco Folino, Andrea Gualtieri, Marco Antonio Mastratisi, Luigi Pontieri:
A Knowledge-Based Framework for Supporting and Analysing Loosely Structured Collaborative Processes. ADBIS (local proceedings) 2008: 140-153 - [c9]Francesco Folino, Gianluigi Greco, Antonella Guzzo, Luigi Pontieri:
Discovering Multi-Perspective Process Models. ICEIS (2) 2008: 70-77 - [c8]Francesco Folino
Discovering Multi-perspective Process Models: The Case of Loosely-Structured Processes. ICEIS 2008: 130-143 - 2007
- [c7]Gianni Costa
Data Mining for Effective Risk Analysis in a Bank Intelligence Scenario. ICDE Workshops 2007: 904-911 - [c6]Gianni Costa, Francesco Folino, Giuseppe Manco, Riccardo Ortale:
A Hierarchical Probabilistic Model for Co-Clustering High-Dimensional Data. SEBD 2007: 88-99 - 2006
- [c5]Francesco Folino
Effective Incremental Clustering for Duplicate Detection in Large Databases. IDEAS 2006: 45-52 - [c4]Francesco Folino, Giuseppe Manco, Luigi Pontieri:
Effective Incremental Clustering for Duplicate Detection in Large Databases. SEBD 2006: 93-104 - 2005
- [c3]Eugenio Cesario
An Incremental Clustering Scheme for Duplicate Detection in Large Databases. IDEAS 2005: 89-95 - [c2]Eugenio Cesario, Francesco Folino, Antonio Locane, Giuseppe Manco, Riccardo Ortale:
RecBoost: A Supervised Approach to Text Segmentation. SEBD 2005: 220-231 - 2004
- [c1]Eugenio Cesario
Putting Enhanced Hypermedia Personalization into Practice via Web Mining. DEXA 2004: 947-956
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