Abstract

AbstractProcess mining techniques have been receiving great attention in the literature for their ability to automatically support process (re)design. The output of these techniques is a concrete workflow schema that models all the possible execution scenarios registered in the logs, and that can be profitably used to support further-coming enactments. In this paper, we face process mining in a slightly different perspective. Indeed, we propose an approach to process mining that combines novel discovery strategies with abstraction methods, with the aim of producing hierarchical views of the process that satisfactorily capture its behavior at different level of details. Therefore, at the highest level of detail, the mined model can support the design of concrete workflows; at lower levels of detail, the views can be used in advanced business process platforms to support monitoring and analysis. Our approach consists of several algorithms which have been integrated into a systems architecture whose description is accounted for in the paper as well.KeywordsInput SchemaSchema TaxonomyAbstraction MethodImplied ActivityProcess Mining TechniqueThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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