According to our database1, Massimo Guarascio authored at least 34 papers between 2009 and 2019.
Legend:Book In proceedings Article PhD thesis Other
Deep Learning on Big Data.
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
Exploiting fractal dimension and a distributed evolutionary approach to classify data streams with concept drifts.
Appl. Soft Comput., 2019
Deep Sequential Modeling for Recommendation.
Proceedings of the 27th Italian Symposium on Advanced Database Systems, 2019
A Predictive Learning Framework for Monitoring Aggregated Performance Indicators over Business Process Events.
Proceedings of the 22nd International Database Engineering & Applications Symposium, 2018
A descriptive clustering approach to the analysis of quantitative business-process deviances.
Proceedings of the Symposium on Applied Computing, 2017
Integrating a Framework for Discovering Alternative App Stores in a Mobile App Monitoring Platform.
Proceedings of the New Frontiers in Mining Complex Patterns - 6th International Workshop, 2017
Deviance-Aware Discovery of High Quality Process Models.
Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 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
A Robust and Versatile Multi-View Learning Framework for the Detection of Deviant Business Process Instances.
Int. J. Cooperative Inf. Syst., 2016
Profiling Human Behavior Through Multidimensional Latent Factor Modeling.
Proceedings of the New Frontiers in Mining Complex Patterns - 5th International Workshop, 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
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
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
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
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
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
ProMetheuS: A Suite for Process Mining Applications.
Proceedings of the CAiSE'12 Forum at the 24<sup>th</sup> International Conference on Advanced Information Systems Engineering (CAiSE), 2012
Mining models of exceptional objects through rule learning.
Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), 2010
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data.
Proceedings of the IIR 2010, 2010
A Block Mixture Model for Pattern Discovery in Preference Data.
Proceedings of the ICDMW 2010, 2010
A Hierarchical Rule-based Framework for Accurate Classification in Imprecise Domains.
Proceedings of the Seventeenth Italian Symposium on Advanced Database Systems, 2009
High Quality True-Positive Prediction for Fiscal Fraud Detection.
Proceedings of the ICDM Workshops 2009, 2009
Rule Learning with Probabilistic Smoothing.
Proceedings of the Data Warehousing and Knowledge Discovery, 11th International Conference, 2009