Putting Enhanced Hypermedia Personalization into Practice via Web Mining. - Eugenio Cesario; Francesco Folino; Riccardo Ortale (DEXA, 2004)

An Incremental Clustering Scheme for Duplicate Detection in Large Databases. - Eugenio Cesario; Francesco Folino; Giuseppe Manco 001; Luigi Pontieri (IDEAS, 2005)

RecBoost: A Supervised Approach to Text Segmentation. - Eugenio Cesario; Francesco Folino; Antonio Locane; Giuseppe Manco 001; Riccardo Ortale (SEBD, 2005)

Effective Incremental Clustering for Duplicate Detection in Large Databases. - Francesco Folino; Giuseppe Manco 001; Luigi Pontieri (SEBD, 2006)

Data Mining for Effective Risk Analysis in a Bank Intelligence Scenario. - Gianni Costa; Francesco Folino; Antonio Locane; Giuseppe Manco 001; Riccardo Ortale (ICDE Workshops, 2007)

A Hierarchical Probabilistic Model for Co-Clustering High-Dimensional Data. - Gianni Costa; Francesco Folino; Giuseppe Manco 001; Riccardo Ortale (SEBD, 2007)

A Knowledge-Based Framework for Supporting and Analysing Loosely Structured Collaborative Processes. - Stefano Basta; Francesco Folino; Andrea Gualtieri; Marco Antonio Mastratisi; Luigi Pontieri (ADBIS (local proceedings), 2008)

Discovering Multi-Perspective Process Models. - Francesco Folino; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (ICEIS (2), 2008)

Discovering Multi-perspective Process Models: The Case of Loosely-Structured Processes. - Francesco Folino; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (ICEIS, 2008)

Boosting text segmentation via progressive classification. - Eugenio Cesario; Francesco Folino; Antonio Locane; Giuseppe Manco 001; Riccardo Ortale (Knowl. Inf. Syst., 2008)

Discovering expressive process models from noised log data. - Francesco Folino; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (IDEAS, 2009)

A Multiobjective and Evolutionary Clustering Method for Dynamic Networks. - Francesco Folino; Clara Pizzuti (ASONAM, 2010)

A comorbidity-based recommendation engine for disease prediction. - Francesco Folino; Clara Pizzuti (CBMS, 2010)

Multiobjective evolutionary community detection for dynamic networks. - Francesco Folino; Clara Pizzuti (GECCO, 2010)

Effective Analysis of Flexible Collaboration Processes by Way of Abstraction and Mining Techniques. - Alfredo Cuzzocrea; Francesco Folino; Luigi Pontieri (ICEIS (2), 2010)

Scalable parallel co-clustering over multiple heterogeneous data types. - Francesco Folino; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (HPCS, 2010)

A Comorbidity Network Approach to Predict Disease Risk. - Francesco Folino; Clara Pizzuti; Maria Ventura (ITBAM, 2010)

Combining Markov Models and Association Analysis for Disease Prediction. - Francesco Folino; Clara Pizzuti (ITBAM, 2011)

Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction. - Francesco Folino; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (Data Knowl. Eng., 2011)

Link Prediction Approaches for Disease Networks. - Francesco Folino; Clara Pizzuti (ITBAM, 2012)

Discovering Context-Aware Models for Predicting Business Process Performances. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (OTM Conferences (1), 2012)

Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (NFMCP, 2012)

Community evolution detection in time-evolving information networks. - Alfredo Cuzzocrea; Francesco Folino (EDBT/ICDT Workshops, 2013)

A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances. - Antonio Bevacqua; Marco Carnuccio; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2013)

A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances. - Antonio Bevacqua; Marco Carnuccio; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS, 2013)

DynamicNet: an effective and efficient algorithm for supporting community evolution detection in time-evolving information networks. - Alfredo Cuzzocrea; Francesco Folino; Clara Pizzuti (IDEAS, 2013)

Discovering High-Level Performance Models for Ticket Resolution Processes. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (OTM Conferences, 2013)

Adaptive Trace Abstraction Approach for Predicting Business Process Performances. - Antonio Bevacqua; Marco Carnuccio; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (SEBD, 2013)

Methods and techniques for discovering taxonomies of behavioral process models. - Francesco Folino; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (WIREs Data Mining Knowl. Discov., 2013)

Mining Predictive Process Models out of Low-level Multidimensional Logs. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (CAiSE, 2014)

A Framework for the Discovery of Predictive Fix-time Models. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2014)

An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (Revised Selected Papers), 2014)

An Evolutionary Multiobjective Approach for Community Discovery in Dynamic Networks. - Francesco Folino; Clara Pizzuti (IEEE Trans. Knowl. Data Eng., 2014)

Mining Multi-variant Process Models from Low-Level Logs. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (BIS, 2015)

A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (EDOC, 2015)

On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2015)

A Multi-view Learning Approach to the Discovery of Deviant Process Instances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (OTM Conferences, 2015)

A recommendation engine for disease prediction. - Francesco Folino; Clara Pizzuti (Inf. Syst. E Bus. Manag., 2015)

A Cloud-Based Prediction Framework for Analyzing Business Process Performances. - Eugenio Cesario; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (CD-ARES, 2016)

A multi-view multi-dimensional ensemble learning approach to mining business process deviances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (IJCNN, 2016)

A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (Int. J. Cooperative Inf. Syst., 2016)

Extensions, Analysis and Experimental Assessment of a Probabilistic Ensemble-learning Framework for Detecting Deviances in Business Process Instances. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (1), 2017)

Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (ICEIS (Revised Selected Papers), 2017)

A Peer-to-Peer Architecture for Detecting Attacks from Network Traffic and Log Data. - Francesco Folino; Gianluigi Folino; Luigi Pontieri; Pietro Sabatino (HPCS, 2017)

A descriptive clustering approach to the analysis of quantitative business-process deviances. - Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (SAC, 2017)

A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (IDEAS, 2018)

An Ensemble-Based P2P Framework for the Detection of Deviant Business Process Instances. - Francesco Folino; Gianluigi Folino; Luigi Pontieri (HPCS, 2018)

Combining Model- and Example-Driven Classification to Detect Security Breaches in Activity-Unaware Logs. - Bettina Fazzinga; Francesco Folino; Filippo Furfaro; Luigi Pontieri (OTM Conferences (2), 2018)

Deviance-Aware Discovery of High-Quality Process Models. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (Int. J. Artif. Intell. Tools, 2018)

Pushing More AI Capabilities into Process Mining to Better Deal with Low-Quality Logs. - Francesco Folino; Luigi Pontieri (Business Process Management Workshops, 2019)

Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (ICTAI, 2019)

Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events. - Alfredo Cuzzocrea; Francesco Folino; Massimo Guarascio 001; Luigi Pontieri (Inf. Syst., 2019)

Business Process Deviance Mining. - Francesco Folino; Luigi Pontieri (Encyclopedia of Big Data Technologies, 2019)

A p2p environment to validate ensemble-based approaches in the cybersecurity domain. - Francesco Folino; Gianluigi Folino; Luigi Pontieri (PDP, 2020)

A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (PKDD/ECML Workshops, 2020)

Exploiting Temporal Convolution for Activity Prediction in Process Analytics. - Francesco Folino; Massimo Guarascio 001; Angelica Liguori; Giuseppe Manco 001; Luigi Pontieri; Ettore Ritacco (PKDD/ECML Workshops, 2020)

An ensemble-based approach to the security-oriented classification of low-level log traces. - Bettina Fazzinga; Francesco Folino; Filippo Furfaro; Luigi Pontieri (Expert Syst. Appl., 2020)

On learning effective ensembles of deep neural networks for intrusion detection. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Francesco Sergio Pisani; Luigi Pontieri (Inf. Fusion, 2021)

AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion. - Francesco Folino; Luigi Pontieri (J. Data Semant., 2021)

Correction to: AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion. - Francesco Folino; Luigi Pontieri (J. Data Semant., 2021)

Detecting DoS and DDoS Attacks through Sparse U-Net-like Autoencoders. - Nunziato Cassavia; Francesco Folino; Massimo Guarascio 001 (ICTAI, 2022)

Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (ISMIS, 2022)

Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (Bus. Inf. Syst. Eng., 2022)

Sparse Mixtures of Shallow Linear Experts for Interpretable and Fast Outcome Prediction. - Francesco Folino; Luigi Pontieri; Pietro Sabatino (ICPM Workshops, 2023)

Explainable Process Deviance Discovery with Data-Efficient Deep Learning. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (NUMTA (1), 2023)

Generating the Traces You Need: A Conditional Generative Model for Process Mining Data. - Riccardo Graziosi; Massimiliano Ronzani; Andrei Buliga 001; Chiara Di Francescomarino; Francesco Folino; Chiara Ghidini; Francesca Meneghello 002; Luigi Pontieri (ICPM, 2024)

A Scalable Vertical Federated Learning Framework for Analytics in the Cybersecurity Domain. - Francesco Folino; Gianluigi Folino; Francesco Sergio Pisani; Pietro Sabatino; Luigi Pontieri (PDP, 2024)

Discussion: Effective and Interpretable Outcome Prediction by Training Sparse Mixtures of Linear Experts. - Francesco Folino; Luigi Pontieri; Pietro Sabatino (CoRR, 2024)

Towards Data- and Compute-Efficient Fake-News Detection: An Approach Combining Active Learning and Pre-Trained Language Models. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri; Paolo Zicari (SN Comput. Sci., 2024)

Data- & compute-efficient deviance mining via active learning and fast ensembles. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (J. Intell. Inf. Syst., 2024)

Efficiently approaching vertical federated learning by combining data reduction and conditional computation techniques. - Francesco Folino; Gianluigi Folino; Francesco Sergio Pisani; Luigi Pontieri; Pietro Sabatino (J. Big Data, 2024)

The force of few: boosting deviance detection in data scarcity scenarios through self-supervised learning and pattern-based encoding. - Francesco Folino; Gianluigi Folino; Massimo Guarascio 001; Luigi Pontieri (Soft Comput., 2025)