Massimo Guarascio

发表

Profiling Human Behavior Through Multidimensional Latent Factor Modeling

Massimo Guarascio, Francesco Sergio Pisani, Ettore Ritacco, 2016, NFMCP@PKDD/ECML.

A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2013, ICEIS.

Adaptive Trace Abstraction Approach for Predicting Business Process Performances

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2013, SEBD.

A Cloud-Based Prediction Framework for Analyzing Business Process Performances

Eugenio Cesario, Francesco Folino, Luigi Pontieri, 2016, CD-ARES.

Discovering High-Level Performance Models for Ticket Resolution Processes

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2013, OTM Conferences.

A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2018, IDEAS.

Context-Aware Predictions on Business Processes: An Ensemble-Based Solution

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2012, NFMCP.

High Quality True-Positive Prediction for Fiscal Fraud Detection

Dino Pedreschi, Fosca Giannotti, Stefano Basta, 2009, 2009 IEEE International Conference on Data Mining Workshops.

Mining Predictive Process Models out of Low-level Multidimensional Logs

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2014, CAiSE.

Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2017, ICEIS.

Deep Autoencoder Ensembles for Anomaly Detection on Blockchain

Massimo Guarascio, Ettore Ritacco, Giuseppe Manco, 2020, ISMIS.

An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2014, ICEIS.

Risk analysis and reliability of the GERDA Experiment extraction and ventilation plant at Gran Sasso mountain underground laboratory of Italian National Institute for Nuclear Physics

Fabio Garzia, Massimo Guarascio, Mara Lombardi, 2017 .

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

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2017, ICEIS.

Exploiting fractal dimension and a distributed evolutionary approach to classify data streams with concept drifts

Massimo Guarascio, Gianluigi Folino, Giuseppe Papuzzo, 2019, Appl. Soft Comput..

Deep Sequential Modeling for Recommendation

Massimo Guarascio, Ettore Ritacco, Giuseppe Manco, 2019, SEBD.

A Prediction Framework for Proactively Monitoring Aggregate Process-Performance Indicators

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2015, 2015 IEEE 19th International Enterprise Distributed Object Computing Conference.

Evaluation of the Stability of UndergroundRock Pillars through a Probabilistic Approach

Massimo Guarascio, Pierpaolo Oreste, 2012 .

Integrating a Framework for Discovering Alternative App Stores in a Mobile App Monitoring Platform

Rocco Mammoliti, Massimo Guarascio, Ettore Ritacco, 2017, NFMCP@PKDD/ECML.

Mining models of exceptional objects through rule learning

Gianni Costa, Riccardo Ortale, Massimo Guarascio, 2010, SAC '10.

Deep Learning on Big Data

Maryam Amir Haeri, Massimo Guarascio, Gianluigi Folino, 2019, Encyclopedia of Big Data Technologies.

Rule Learning with Probabilistic Smoothing

Gianni Costa, Riccardo Ortale, Massimo Guarascio, 2009, DaWaK.

Knowledge Discovery in Databases

Massimo Guarascio, Ettore Ritacco, Giuseppe Manco, 2019, Encyclopedia of Bioinformatics and Computational Biology.

Deep Learning

Massimo Guarascio, Ettore Ritacco, Giuseppe Manco, 2019, Encyclopedia of Bioinformatics and Computational Biology.

A Framework for the Discovery of Predictive Fix-time Models

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2014, ICEIS.

Mining Multi-variant Process Models from Low-Level Logs

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2015, BIS.

A Block Mixture Model for Pattern Discovery in Preference Data

Nicola Barbieri, Massimo Guarascio, Giuseppe Manco, 2010, 2010 IEEE International Conference on Data Mining Workshops.

Network Models

Massimo Guarascio, Ettore Ritacco, Giuseppe Manco, 2019, Encyclopedia of Bioinformatics and Computational Biology.

A Multi-view Learning Approach to the Discovery of Deviant Process Instances

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2015, OTM Conferences.

A Data-Driven Prediction Framework for Analyzing and Monitoring Business Process Performances

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2013, ICEIS.

Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2018, Inf. Syst..

On the Discovery of Explainable and Accurate Behavioral Models for Complex Lowly-structured Business Processes

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2015, ICEIS.

Discovering Context-Aware Models for Predicting Business Process Performances

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2012, OTM Conferences.

A multi-view multi-dimensional ensemble learning approach to mining business process deviances

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Deviance-Aware Discovery of High Quality Process Models

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

ProMetheuS: A Suite for Process Mining Applications

Gianluigi Greco, Massimo Guarascio, Lucantonio Ghionna, 2012, CAiSE Forum.

A Hierarchical Rule-based Framework for Accurate Classification in Imprecise Domains

Gianni Costa, Riccardo Ortale, Massimo Guarascio, 2009, SEBD.

Network Topology

Massimo Guarascio, Ettore Ritacco, Giuseppe Manco, 2019, Encyclopedia of Bioinformatics and Computational Biology.

A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2016, Int. J. Cooperative Inf. Syst..

Deviance-Aware Discovery of High-Quality Process Models

Francesco Folino, Alfredo Cuzzocrea, Luigi Pontieri, 2018, Int. J. Artif. Intell. Tools.

An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data

Nicola Barbieri, Massimo Guarascio, Ettore Ritacco, 2010, IIR.

A descriptive clustering approach to the analysis of quantitative business-process deviances

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2017, SAC.

Sanitization of Images Containing Stegomalware via Machine Learning Approaches

Luca Caviglione, Massimo Guarascio, Giuseppe Manco, 2021, ITASEC.

Discovering accurate deep learning based predictive models for automatic customer support ticket classification

Luigi Pontieri, Massimo Guarascio, Paolo Zicari, 2021, SAC.

On learning effective ensembles of deep neural networks for intrusion detection

Francesco Folino, Luigi Pontieri, Massimo Guarascio, 2021, Inf. Fusion.

Advanced geostatistics in the mining industry : proceedings of the NATO Advanced Study Institute held at the Istituto di Geologia Applicata of the University of Rome, Italy, 13-25 October 1975

Massimo Guarascio, Michel David, C. Huijbregts, 1976 .

Advanced Geostatistics in the Mining Industry

Massimo Guarascio, J. R. Alldredge, M. David, 1977 .