Process-level Model Repair through Instance Graph Representation: (Discussion paper)

Laura Genga, Claudia Diamantini (Corresponderende auteur), E. Storti, Domenico Potena

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Downloads (Pure)

Samenvatting

Existing model repair techniques propose changes that are based on event-level deviations observed in a log, like inserted or skipped events, often overlooking process precision at the advantage of fitness. The present short paper aims to briefly introduce the recent proposal of an alternative approach targeting higher-level structured anomalous behaviors. To do this, the approach exploits instance graph representation of anomalous behaviors, that can be derived from the event log and the original process model. The approach demonstrates that repaired models obtained in this way show higher precision and simplicity, with only small reduction of process fitness.

Originele taal-2Engels
TitelSEBD 2024 : Symposium on Advanced Database Systems 2024
SubtitelProceedings of the 32nd Symposium on Advanced Database Systems
RedacteurenMaurizio Atzori, Paolo Ciaccia, Michelangelo Ceci, Federica Mandreoli, Donato Malerba, Manuela Sanguinetti, Antonio Pellicani, Federico Motta
UitgeverijCEUR-WS.org
Pagina's359-367
Aantal pagina's9
StatusGepubliceerd - 2024
Evenement32nd Italian Symposium on Advanced Database Systems, SEBD 2024 - Villasimius, Italië
Duur: 23 jun. 202426 jun. 2024

Publicatie series

NaamCEUR Workshop Proceedings
Volume3741
ISSN van elektronische versie1613-0073

Congres

Congres32nd Italian Symposium on Advanced Database Systems, SEBD 2024
Land/RegioItalië
StadVillasimius
Periode23/06/2426/06/24

Vingerafdruk

Duik in de onderzoeksthema's van 'Process-level Model Repair through Instance Graph Representation: (Discussion paper)'. Samen vormen ze een unieke vingerafdruk.

Citeer dit