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dc.creatorSchönig, Stefanes
dc.creatorCabanillas Macías, Cristinaes
dc.creatorMendling, Janes
dc.date.accessioned2020-11-13T08:49:56Z
dc.date.available2020-11-13T08:49:56Z
dc.date.issued2016
dc.identifier.citationSchönig, S., Cabanillas Macías, C. y Mendling, J. (2016). A framework for efficiently mining the organisational perspective of business processes. Decision Support Systems, 89 (September 2016), 87-97.
dc.identifier.issn0167-9236es
dc.identifier.urihttps://hdl.handle.net/11441/102599
dc.description.abstractProcess mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions, which is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they do not aim at providing efficient solutions; or (iii) the discovered process models are difficult to read due to the number of assignment conditions included. In this paper we address these problems and develop an efficient and effective process mining framework that provides extensive support for the discovery of patterns related to resource assignment. The framework is validated in terms of performance and applicability.es
dc.description.sponsorshipEuropean Union 1502/89304-01/2012 (KpPQ)es
dc.description.sponsorshipAustrian Research Promotion Agency (FFG) 845638 (SHAPE)es
dc.formatapplication/pdfes
dc.format.extent34es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofDecision Support Systems, 89 (September 2016), 87-97.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBusiness Process Managementes
dc.subjectDeclarative process mininges
dc.subjectEvent log analysises
dc.subjectOrganisational perspectivees
dc.subjectResource perspectivees
dc.titleA framework for efficiently mining the organisational perspective of business processeses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.projectID1502/89304-01/2012 (KpPQ)es
dc.relation.projectID845638 (SHAPE)es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S016792361630104Xes
dc.identifier.doi10.1016/j.dss.2016.06.012es
dc.journaltitleDecision Support Systemses
dc.publication.volumen89es
dc.publication.issueSeptember 2016es
dc.publication.initialPage87es
dc.publication.endPage97es
dc.contributor.funderEuropean Union (UE)es
dc.contributor.funderAustrian Research Promotion Agency (FFG)es

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