Applying Clustering in Process Mining to Find Different Versions of a Business Process That Changes over Time

dc.catalogadorjlo
dc.contributor.authorLuengo Mundaca, Daniela Lorena
dc.contributor.authorSepúlveda Fernández, Marcos Ernesto
dc.date.accessioned2024-06-12T19:06:14Z
dc.date.available2024-06-12T19:06:14Z
dc.date.issued2012
dc.description.abstractMost Process Mining techniques assume business processes remain steady through time, when in fact their underlying design could evolve over time. Discovery algorithms should be able to automatically find the different versions of a process, providing independent models to describe each of them. In this article, we present an approach that uses the starting time of each process instance as an additional feature to those considered in traditional clustering approaches. By combining control-flow and time features, the clusters formed share both a structural similarity and a temporal proximity. Hence, the process model generated for each cluster should represent a different version of the analyzed business process. A synthetic example set was used for testing, showing the new approach outperforms the basic approach. Although further testing with real data is required, these results motivate us to deepen on this research line.
dc.description.funderPropio
dc.fuente.origenHistorial Académico
dc.identifier.isbn978-3642281075
dc.identifier.issn1865-1348
dc.identifier.urihttp://link.springer.com/chapter/10.1007%2F978-3-642-28108-2_15?LI=true
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/86742
dc.identifier.wosidWOS:000310558400015
dc.information.autorucEscuela de Ingeniería; Luengo Mundaca, Daniela Lorena; S/I; 154905
dc.information.autorucEscuela de Ingeniería; Sepúlveda Fernández, Marcos Ernesto; 0000-0002-9467-7666; 80415
dc.issue.numero1
dc.language.isound
dc.nota.accesocontenido parcial
dc.publisherSpringer
dc.relation.ispartofBusiness Process Management Workshops
dc.rightsacceso restringido
dc.subject.ddc650
dc.subject.deweyAdministraciónes_ES
dc.titleApplying Clustering in Process Mining to Find Different Versions of a Business Process That Changes over Time
dc.typecapítulo de libro
sipa.codpersvinculados154905
sipa.codpersvinculados80415
sipa.trazabilidadHistorial Académico;09-07-2021
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