Search Results for author: Fabrizio Maria Maggi

Found 13 papers, 6 papers with code

Monitoring Hybrid Process Specifications with Conflict Management: The Automata-theoretic Approach

no code implementations25 Nov 2021 Anti Alman, Fabrizio Maria Maggi, Marco Montali, Fabio Patrizi, Andrey Rivkin

For example, in the medical domain, a clinical guideline describing the treatment of a specific disease cannot account for all possible co-factors that can coexist for a specific patient and therefore additional constraints may need to be considered.

Temporal Logic

Exploring Business Process Deviance with Sequential and Declarative Patterns

1 code implementation24 Nov 2021 Giacomo Bergami, Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi, Joonas Puura

Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to {their} expected or desirable outcomes.

Process discovery on deviant traces and other stranger things

no code implementations30 Sep 2021 Federico Chesani, Chiara Di Francescomarino, Chiara Ghidini, Daniela Loreti, Fabrizio Maria Maggi, Paola Mello, Marco Montali, Sergio Tessaris

As the need to understand and formalise business processes into a model has grown over the last years, the process discovery research field has gained more and more importance, developing two different classes of approaches to model representation: procedural and declarative.

How do I update my model? On the resilience of Predictive Process Monitoring models to change

no code implementations8 Sep 2021 Williams Rizzi1, Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi

Existing well investigated Predictive Process Monitoring techniques typically construct a predictive model based on past process executions, and then use it to predict the future of new ongoing cases, without the possibility of updating it with new cases when they complete their execution.

Incremental Learning Predictive Process Monitoring

Automated Discovery of Data Transformations for Robotic Process Automation

no code implementations3 Jan 2020 Volodymyr Leno, Marlon Dumas, Marcello La Rosa, Fabrizio Maria Maggi, Artem Polyvyanyy

In this setting, this paper addresses the problem of analyzing User Interaction (UI) logs in order to discover routines where a user transfers data from one spreadsheet or (Web) form to another.

Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring

1 code implementation23 May 2019 Stephan A. Fahrenkrog-Petersen, Niek Tax, Irene Teinemaa, Marlon Dumas, Massimiliano de Leoni, Fabrizio Maria Maggi, Matthias Weidlich

Predictive process monitoring is a family of techniques to analyze events produced during the execution of a business process in order to predict the future state or the final outcome of running process instances.

Predictive Process Monitoring

Semantic DMN: Formalizing and Reasoning About Decisions in the Presence of Background Knowledge

no code implementations31 Jul 2018 Diego Calvanese, Marlon Dumas, Fabrizio Maria Maggi, Marco Montali

The Decision Model and Notation (DMN) is a recent OMG standard for the elicitation and representation of decision models, and for managing their interconnection with business processes.

Incremental Predictive Process Monitoring: How to Deal with the Variability of Real Environments

no code implementations11 Apr 2018 Chiara Di Francescomarino, Chiara Ghidini, Fabrizio Maria Maggi, Williams Rizzi, Cosimo Damiano Persia

The results provide a first evidence of the potential of incremental learning strategies for predicting process monitoring in real environments, and of the impact of different case encoding strategies in this setting.

Incremental Learning Predictive Process Monitoring

Alarm-Based Prescriptive Process Monitoring

2 code implementations23 Mar 2018 Irene Teinemaa, Niek Tax, Massimiliano de Leoni, Marlon Dumas, Fabrizio Maria Maggi

Predictive process monitoring is concerned with the analysis of events produced during the execution of a process in order to predict the future state of ongoing cases thereof.

Predictive Process Monitoring

Temporal Stability in Predictive Process Monitoring

1 code implementation12 Dec 2017 Irene Teinemaa, Marlon Dumas, Anna Leontjeva, Fabrizio Maria Maggi

We then show that temporal stability can be enhanced by hyperparameter-optimizing random forests and XGBoost classifiers with respect to inter-run stability.

Predictive Process Monitoring Time Series

Outcome-Oriented Predictive Process Monitoring: Review and Benchmark

1 code implementation21 Jul 2017 Irene Teinemaa, Marlon Dumas, Marcello La Rosa, Fabrizio Maria Maggi

Predictive business process monitoring refers to the act of making predictions about the future state of ongoing cases of a business process, based on their incomplete execution traces and logs of historical (completed) traces.

Predictive Process Monitoring

Business Process Deviance Mining: Review and Evaluation

1 code implementation29 Aug 2016 Hoang Nguyen, Marlon Dumas, Marcello La Rosa, Fabrizio Maria Maggi, Suriadi Suriadi

Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to its expected or desirable outcomes.

General Classification

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