We propose Answer Set Programming (ASP) as an approach for modeling and solving problems from the area of Declarative Process Mining (DPM). We consider here three classical problems, namely, Log Generation, Conformance Checking, and Query Checking. These problems are addressed from both a control-flow and a data-aware perspective. The approach is based on the representation of process specifications as (finite-state) automata. Since these are strictly more expressive than the de facto DPM standard specification language DECLARE, more general specifications than those typical of DPM can be handled, such as formulas in linear-time temporal logic over finite traces. (Full version available in the Proceedings of the 36th AAAI Conference on Artificial Intelligence).

ASP-Based Declarative Process Mining (Extended Abstract) / Chiariello, Francesco; Maggi, FABRIZIO MARIA; Patrizi, Fabio. - (2022). (Intervento presentato al convegno International Conference on Logic Programming tenutosi a Haifa; Israel).

ASP-Based Declarative Process Mining (Extended Abstract)

Francesco Chiariello;Fabrizio Maria Maggi;Fabio Patrizi
2022

Abstract

We propose Answer Set Programming (ASP) as an approach for modeling and solving problems from the area of Declarative Process Mining (DPM). We consider here three classical problems, namely, Log Generation, Conformance Checking, and Query Checking. These problems are addressed from both a control-flow and a data-aware perspective. The approach is based on the representation of process specifications as (finite-state) automata. Since these are strictly more expressive than the de facto DPM standard specification language DECLARE, more general specifications than those typical of DPM can be handled, such as formulas in linear-time temporal logic over finite traces. (Full version available in the Proceedings of the 36th AAAI Conference on Artificial Intelligence).
2022
International Conference on Logic Programming
04 Pubblicazione in atti di convegno::04d Abstract in atti di convegno
ASP-Based Declarative Process Mining (Extended Abstract) / Chiariello, Francesco; Maggi, FABRIZIO MARIA; Patrizi, Fabio. - (2022). (Intervento presentato al convegno International Conference on Logic Programming tenutosi a Haifa; Israel).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1664268
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