Search Results for author: Fabrizio Maggi

Found 2 papers, 0 papers with code

Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring

no code implementations8 May 2018 Ilya Verenich, Marlon Dumas, Marcello La Rosa, Fabrizio Maggi, Irene Teinemaa

Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining cycle time of a given process case.

LTLf and LDLf Monitoring: A Technical Report

no code implementations30 Apr 2014 Giuseppe De Giacomo, Riccardo De Masellis, Marco Grasso, Fabrizio Maggi, Marco Montali

LDLf is a powerful logic that captures all monadic second order logic on finite traces, which is obtained by combining regular expressions and LTLf, adopting the syntax of propositional dynamic logic (PDL).


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