Francesco Folino

Orcid: 0000-0002-4952-1187

According to our database1, Francesco Folino authored at least 63 papers between 2004 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs.
Bus. Inf. Syst. Eng., 2022

Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery.
Proceedings of the Foundations of Intelligent Systems - 26th International Symposium, 2022

Detecting DoS and DDoS Attacks through Sparse U-Net-like Autoencoders.
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

2021
Correction to: AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion.
J. Data Semant., 2021

AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion.
J. Data Semant., 2021

On learning effective ensembles of deep neural networks for intrusion detection.
Inf. Fusion, 2021

2020
An ensemble-based approach to the security-oriented classification of low-level log traces.
Expert Syst. Appl., 2020

Exploiting Temporal Convolution for Activity Prediction in Process Analytics.
Proceedings of the ECML PKDD 2020 Workshops, 2020

A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances.
Proceedings of the ECML PKDD 2020 Workshops, 2020

A p2p environment to validate ensemble-based approaches in the cybersecurity domain.
Proceedings of the 28th Euromicro International Conference on Parallel, 2020

2019
Business Process Deviance Mining.
Proceedings of the Encyclopedia of Big Data Technologies., 2019

Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events.
Inf. Syst., 2019

Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data.
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

Pushing More AI Capabilities into Process Mining to Better Deal with Low-Quality Logs.
Proceedings of the Business Process Management Workshops, 2019

2018
Deviance-Aware Discovery of High-Quality Process Models.
Int. J. Artif. Intell. Tools, 2018

Combining Model- and Example-Driven Classification to Detect Security Breaches in Activity-Unaware Logs.
Proceedings of the On the Move to Meaningful Internet Systems. OTM 2018 Conferences, 2018

An Ensemble-Based P2P Framework for the Detection of Deviant Business Process Instances.
Proceedings of the 2018 International Conference on High Performance Computing & Simulation, 2018

A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events.
Proceedings of the 22nd International Database Engineering & Applications Symposium, 2018

2017
A descriptive clustering approach to the analysis of quantitative business-process deviances.
Proceedings of the Symposium on Applied Computing, 2017

A Peer-to-Peer Architecture for Detecting Attacks from Network Traffic and Log Data.
Proceedings of the 2017 International Conference on High Performance Computing & Simulation, 2017

Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning.
Proceedings of the Enterprise Information Systems - 19th International Conference, 2017

Extensions, Analysis and Experimental Assessment of a Probabilistic Ensemble-learning Framework for Detecting Deviances in Business Process Instances.
Proceedings of the ICEIS 2017, 2017

2016
A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances.
Int. J. Cooperative Inf. Syst., 2016

A multi-view multi-dimensional ensemble learning approach to mining business process deviances.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

A Cloud-Based Prediction Framework for Analyzing Business Process Performances.
Proceedings of the Availability, Reliability, and Security in Information Systems, 2016

2015
A recommendation engine for disease prediction.
Inf. Syst. E Bus. Manag., 2015

A Multi-view Learning Approach to the Discovery of Deviant Process Instances.
Proceedings of the On the Move to Meaningful Internet Systems: OTM 2015 Conferences, 2015

On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes.
Proceedings of the ICEIS 2015, 2015

A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators.
Proceedings of the 19th IEEE International Enterprise Distributed Object Computing Conference, 2015

Mining Multi-variant Process Models from Low-Level Logs.
Proceedings of the Business Information Systems - 18th International Conference, 2015

2014
An Evolutionary Multiobjective Approach for Community Discovery in Dynamic Networks.
IEEE Trans. Knowl. Data Eng., 2014

An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models.
Proceedings of the Enterprise Information Systems - 16th International Conference, 2014

A Framework for the Discovery of Predictive Fix-time Models.
Proceedings of the ICEIS 2014, 2014

Mining Predictive Process Models out of Low-level Multidimensional Logs.
Proceedings of the Advanced Information Systems Engineering, 2014

2013
Methods and techniques for discovering taxonomies of behavioral process models.
WIREs Data Mining Knowl. Discov., 2013

Adaptive Trace Abstraction Approach for Predicting Business Process Performances.
Proceedings of the 21st Italian Symposium on Advanced Database Systems, 2013

Discovering High-Level Performance Models for Ticket Resolution Processes.
Proceedings of the On the Move to Meaningful Internet Systems: OTM 2013 Conferences, 2013

<i>DynamicNet</i>: an effective and efficient algorithm for supporting community evolution detection in time-evolving information networks.
Proceedings of the 17th International Database Engineering & Applications Symposium, 2013

A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances.
Proceedings of the Enterprise Information Systems - 15th International Conference, 2013

A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances.
Proceedings of the ICEIS 2013, 2013

Community evolution detection in time-evolving information networks.
Proceedings of the Joint 2013 EDBT/ICDT Conferences, 2013

2012
Context-Aware Predictions on Business Processes: An Ensemble-Based Solution.
Proceedings of the New Frontiers in Mining Complex Patterns - First International Workshop, 2012

Discovering Context-Aware Models for Predicting Business Process Performances.
Proceedings of the On the Move to Meaningful Internet Systems: OTM 2012, 2012

Link Prediction Approaches for Disease Networks.
Proceedings of the Information Technology in Bio- and Medical Informatics, 2012

2011
Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction.
Data Knowl. Eng., 2011

Combining Markov Models and Association Analysis for Disease Prediction.
Proceedings of the Information Technology in Bio- and Medical Informatics, 2011

2010
A Comorbidity Network Approach to Predict Disease Risk.
Proceedings of the Information Technology in Bio- and Medical Informatics, 2010

Scalable parallel co-clustering over multiple heterogeneous data types.
Proceedings of the 2010 International Conference on High Performance Computing & Simulation, 2010

Effective Analysis of Flexible Collaboration Processes by Way of Abstraction and Mining Techniques.
Proceedings of the ICEIS 2010 - Proceedings of the 12th International Conference on Enterprise Information Systems, Volume 2, AIDSS, Funchal, Madeira, Portugal, June 8, 2010

Multiobjective evolutionary community detection for dynamic networks.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

A comorbidity-based recommendation engine for disease prediction.
Proceedings of the IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), 2010

A Multiobjective and Evolutionary Clustering Method for Dynamic Networks.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2010

2009
Discovering expressive process models from noised log data.
Proceedings of the International Database Engineering and Applications Symposium (IDEAS 2009), 2009

2008
Boosting text segmentation via progressive classification.
Knowl. Inf. Syst., 2008

Discovering Multi-perspective Process Models: The Case of Loosely-Structured Processes.
Proceedings of the Enterprise Information Systems, 10th International Conference, 2008

Discovering Multi-Perspective Process Models.
Proceedings of the ICEIS 2008, 2008

A Knowledge-Based Framework for Supporting and Analysing Loosely Structured Collaborative Processes.
Proceedings of the Advances in Databases and Information Systems, 2008

2007
A Hierarchical Probabilistic Model for Co-Clustering High-Dimensional Data.
Proceedings of the Fifteenth Italian Symposium on Advanced Database Systems, 2007

Data Mining for Effective Risk Analysis in a Bank Intelligence Scenario.
Proceedings of the 23rd International Conference on Data Engineering Workshops, 2007

2006
Effective Incremental Clustering for Duplicate Detection in Large Databases.
Proceedings of the Tenth International Database Engineering and Applications Symposium (IDEAS 2006), 2006

2005
RecBoost: A Supervised Approach to Text Segmentation.
Proceedings of the Thirteenth Italian Symposium on Advanced Database Systems, 2005

An Incremental Clustering Scheme for Duplicate Detection in Large Databases.
Proceedings of the Ninth International Database Engineering and Applications Symposium (IDEAS 2005), 2005

2004
Putting Enhanced Hypermedia Personalization into Practice via Web Mining.
Proceedings of the Database and Expert Systems Applications, 15th International Conference, 2004


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