A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes

Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are called concept drifts and its detection is a big c...

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Detalles Bibliográficos
Autores: Víctor Gallego Fontenla, Vidal Aguiar, Juan Carlos, Lama Penín, Manuel
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/39158
Acceso en línea:https://hdl.handle.net/10347/39158
Access Level:acceso abierto
Palabra clave:Business processes
Concept drift
Process mining
Conformance checking-based detection
120304 Inteligencia artificial
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spelling A Conformance Checking-Based Approach for Sudden Drift Detection in Business ProcessesVíctor Gallego FontenlaVidal Aguiar, Juan CarlosLama Penín, ManuelBusiness processesConcept driftProcess miningConformance checking-based detection120304 Inteligencia artificialReal life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. In this article, we present C2D2 (Conformance Checking-based Drift Detection), a new approach to detect sudden control-flow changes in the process models from event traces. C2D2 combines discovery techniques with conformance checking methods to perform an offline detection. Our approach has been validated with a synthetic benchmarking dataset formed by 68 logs, showing an improvement in the accuracy while maintaining a very low delay in the drift detection.IEEEUniversidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS)Universidade de Santiago de Compostela. Departamento de Electrónica e Computación20232023-02-0620232023-02-06journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10347/39158reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostelainstname:Universidad de Santiago de Compostela (USC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:minerva.usc.gal:10347/391582026-06-15T12:47:27Z
dc.title.none.fl_str_mv A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
title A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
spellingShingle A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
Víctor Gallego Fontenla
Business processes
Concept drift
Process mining
Conformance checking-based detection
120304 Inteligencia artificial
title_short A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
title_full A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
title_fullStr A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
title_full_unstemmed A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
title_sort A Conformance Checking-Based Approach for Sudden Drift Detection in Business Processes
dc.creator.none.fl_str_mv Víctor Gallego Fontenla
Vidal Aguiar, Juan Carlos
Lama Penín, Manuel
author Víctor Gallego Fontenla
author_facet Víctor Gallego Fontenla
Vidal Aguiar, Juan Carlos
Lama Penín, Manuel
author_role author
author2 Vidal Aguiar, Juan Carlos
Lama Penín, Manuel
author2_role author
author
dc.contributor.none.fl_str_mv Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS)
Universidade de Santiago de Compostela. Departamento de Electrónica e Computación
dc.subject.none.fl_str_mv Business processes
Concept drift
Process mining
Conformance checking-based detection
120304 Inteligencia artificial
topic Business processes
Concept drift
Process mining
Conformance checking-based detection
120304 Inteligencia artificial
description Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are called concept drifts and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. In this article, we present C2D2 (Conformance Checking-based Drift Detection), a new approach to detect sudden control-flow changes in the process models from event traces. C2D2 combines discovery techniques with conformance checking methods to perform an offline detection. Our approach has been validated with a synthetic benchmarking dataset formed by 68 logs, showing an improvement in the accuracy while maintaining a very low delay in the drift detection.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-02-06
2023
2023-02-06
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10347/39158
url https://hdl.handle.net/10347/39158
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname:Universidad de Santiago de Compostela (USC)
instname_str Universidad de Santiago de Compostela (USC)
reponame_str Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
collection Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,198674

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