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dc.rights.licenseReconocimiento 4.0 Internacional. (CC BY)-
dc.contributor.authorCalegari, Danieles
dc.contributor.authorDelgado, Andreaes
dc.date.accessioned2024-11-22T18:04:11Z-
dc.date.available2024-11-22T18:04:11Z-
dc.date.issued2024-
dc.identifier.urihttps://hdl.handle.net/20.500.12381/3704-
dc.description.abstractProcess mining on business process execution data has focused primarily on orchestration-type processes performed in a single organization (intra-organizational). Collaborative (inter-organizational) processes, unlike those of orchestration type, expand several organizations (for example, in e-Government), adding complexity and various challenges both for their implementation and for their discovery, prediction, and analysis of their execution. Predictive process monitoring is based on exploiting execution data from past instances to predict the execution of current cases. It is possible to make predictions on the next activity and remaining time, among others, to anticipate possible deviations, violations, and delays in the processes to take preventive measures (e.g., re-allocation of resources). In this work, we propose an extension for collaborative processes of traditional process prediction, considering particularities of this type of process, which add information of interest in this context, for example, the next activity of which participant or the following message to be exchanged between two participants.es
dc.description.sponsorshipAgencia Nacional de Investigación e Innovaciónes
dc.language.isoenges
dc.relation.urihttps://hdl.handle.net/20.500.12381/3700es
dc.relation.urihttps://hdl.handle.net/20.500.12381/3701es
dc.relation.urihttps://hdl.handle.net/20.500.12381/3702es
dc.relation.urihttps://hdl.handle.net/20.500.12381/3703es
dc.rightsAcceso abierto*
dc.source6th International Conference on Process Mining (ICPM), 3rd Workshop on Collaboration Mining for Distributed Systems (COMINDS), Copenhague, Dinamarca, 14 al 18 de Octubre, 2024es
dc.subjectProcess mininges
dc.subjectInter-organizational collaborative processeses
dc.subjectPredictive process monitoringes
dc.titleExtending predictive process monitoring for collaborative processeses
dc.typeDocumento de conferenciaes
dc.subject.aniiCiencias Naturales y Exactas
dc.subject.aniiCiencias de la Computación e Información
dc.subject.aniiCiencias de la Computación
dc.identifier.aniiFMV_1_2021_1_167483es
dc.type.versionPublicadoes
dc.identifier.doihttps://doi.org/10.48550/arXiv.2409.09212-
dc.anii.institucionresponsableUniversidad de la República. Facultad de Ingeniería. Instituto de Computaciónes
dc.anii.subjectcompleto//Ciencias Naturales y Exactas/Ciencias de la Computación e Información/Ciencias de la Computaciónes
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