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2020-03-31 - Colloque/Article dans les actes avec comité de lecture - Anglais - 8 page(s)

Delcoucq Landelin , Lecron Fabian , Fortemps Philippe , van der Aalst Wil.M.P., "Resource-centric process mining: clustering using local process models" in ACM Symposium on Applied Computing, Brno, czech republic, 2020

  • Codes CREF : Sciences de l'ingénieur (DI2000)
  • Unités de recherche UMONS : Management de l'Innovation Technologique (F113)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech)
Texte intégral :

Abstract(s) :

(Anglais) In this paper, we focus on the resource perspective in the context of process mining. Most process mining techniques focus on the control-flow to uncover problems related to performance or compliance. However, the behavior of resources (e.g., employees) influences the effectiveness and efficiency of processes and should not be considered as secondary. We aim to identify resources exhibiting similar behavioral patterns that go beyond just looking at the mix of activities performed. We want to be able to identify subgroups of resources that perform similar activities but in a different order. We also provide a comparison between existing ways of grouping resources into roles and our resource-centered approach that takes into account the order in which work is performed. We will compare the results of clustering based only on the activities performed and clustering based on local process models that identify work patterns. Experiments are considered on synthetic and real data.