Conformance checking is the problem of verifying if the actual executions of business processes, which are recorded by information systems in dedicated event logs, are compliant with a process model that encodes the process’ constraints. Within conformance checking, alignment-based techniques can exactly pinpoint where deviations are observed. Existing alignment-based techniques rely on the assumption of a perfect knowledge of the order with which process’ activities were executed in reality. However, experience shows that, due to logging errors and inaccuracies, it is not always possible to determine the exact order with which certain activities were executed. This paper illustrates an alignment-based technique where the perfect knowledge assumption of the execution’s order is removed. The technique transforms the problem of alignment-based conformance checking into a planning problem encoded in PDDL, for which planners can find a correct solution in a finite amount of time. We implemented the technique as a software tool that is integrated with state-of-the-art planners. To showcase its practical relevance and scalability, we report on experiments with a real-life case study and several synthetic ones of increasing complexity.

Aligning partially-ordered process-execution traces and models using automated planning / DE LEONI, Massimiliano; Lanciano, Giacomo; Marrella, Andrea. - STAMPA. - (2018), pp. 321-329. (Intervento presentato al convegno 28th International Conference on Automated Planning and Scheduling (ICAPS 2018) tenutosi a Delft, the Netherlands).

Aligning partially-ordered process-execution traces and models using automated planning

Massimiliano de Leoni;Giacomo Lanciano;ANDREA MARRELLA
2018

Abstract

Conformance checking is the problem of verifying if the actual executions of business processes, which are recorded by information systems in dedicated event logs, are compliant with a process model that encodes the process’ constraints. Within conformance checking, alignment-based techniques can exactly pinpoint where deviations are observed. Existing alignment-based techniques rely on the assumption of a perfect knowledge of the order with which process’ activities were executed in reality. However, experience shows that, due to logging errors and inaccuracies, it is not always possible to determine the exact order with which certain activities were executed. This paper illustrates an alignment-based technique where the perfect knowledge assumption of the execution’s order is removed. The technique transforms the problem of alignment-based conformance checking into a planning problem encoded in PDDL, for which planners can find a correct solution in a finite amount of time. We implemented the technique as a software tool that is integrated with state-of-the-art planners. To showcase its practical relevance and scalability, we report on experiments with a real-life case study and several synthetic ones of increasing complexity.
2018
28th International Conference on Automated Planning and Scheduling (ICAPS 2018)
Process Mining; Trace Alignment; Partially-ordered traces; Automated Planning in AI
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Aligning partially-ordered process-execution traces and models using automated planning / DE LEONI, Massimiliano; Lanciano, Giacomo; Marrella, Andrea. - STAMPA. - (2018), pp. 321-329. (Intervento presentato al convegno 28th International Conference on Automated Planning and Scheduling (ICAPS 2018) tenutosi a Delft, the Netherlands).
File allegati a questo prodotto
File Dimensione Formato  
deLeoni_Aligning-partially-ordered_2018.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 831.44 kB
Formato Adobe PDF
831.44 kB Adobe PDF   Contatta l'autore
ICAP_Frontespizio-indice_2018.pdf

solo gestori archivio

Note: https://aaai.org/Library/ICAPS/icaps18contents.php
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 132.31 kB
Formato Adobe PDF
132.31 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1122761
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 16
  • ???jsp.display-item.citation.isi??? 9
social impact