A Modular SMT-based Approach for Data-aware Conformance Checking

Paolo Felli; Alessandro Gianola; Marco Montali; Andrey Rivkin; Sarah Maria Winkler

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A Modular SMT-based Approach for Data-aware Conformance Checking

Abstract

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A Modular SMT-based Approach for Data-aware Conformance Checking

Paolo Felli, Alessandro Gianola, Marco Montali, Andrey Rivkin and Sarah Maria Winkler

Short paper proceedings of the 4th workshop on artificial intelligence and formal verification, logic, automata, and synthesis (OVERLAY), Vol.3311, pp.87-92

3311

4th Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis- 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022) (Udine, 28/11/2022–28/11/2022)

2022

Handle:

https://hdl.handle.net/10863/38674

Abstract

In the last years, automated reasoning techniques have been gaining momentum in the BPM community. One of their recent applications is related to Process Mining. In this work we briefly describe how the conformance checking problem can be addressed using satisfiability modulo theories (SMT).

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Title: A Modular SMT-based Approach for Data-aware Conformance Checking
Creators: Paolo Felli
Alessandro Gianola
Marco Montali
Andrey Rivkin
Sarah Maria Winkler
Publication Details: Short paper proceedings of the 4th workshop on artificial intelligence and formal verification, logic, automata, and synthesis (OVERLAY), Vol.3311, pp.87-92
Editor(s): Geatti L, Sciavicco G, Umbrico A
Conference: 4th Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis- 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022) (Udine, 28/11/2022–28/11/2022)
Series / Volume: 3311
Publisher: CEUR Electronic Workshop Proceedings
Number of pages: 6
Identifiers: (UNIBZ)70884869
991006715698701241
Scopus ID: n.a.
Copyright: 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Academic Unit: Faculty of Computer Science
Faculty of Computer Science
Faculty of Computer Science
Faculty of Computer Science
Faculty of Computer Science
Language: English
Resource Type: Abstract
Author Names String: Felli P, Gianola A, Montali M, Rivkin A, Winkler S
Additional Description: Editors/Supervisors: Geatti L, Sciavicco G, Umbrico A
description: Record is part of a bulk validation set

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