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Knowledge Extraction from Events Flows

  • Alireza Rezaei Mahdiraji
  • Bruno Rossi
  • Alberto Sillitti
  • Giancarlo Succi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7200)

Abstract

In this chapter, we propose an analysis of the approaches and methods available for the automated extraction of knowledge from event flows. We specifically focus on the reconstruction of processes from automatically generated events logs. In this context, we consider that knowledge can be directly gathered by means of the reconstruction of business process models. In the ArtDECO project, we frame such approaches inside delta analysis, that is the detection of differences of the executed processes from the planned models. To this end, we provide an overview of the different techniques available for process reconstruction, and propose an approach for the detection of deviations. To show its effectiveness, we instantiate the usage to the ArtDECO case study.

Keywords

Business Process Process Mining Execution Trace Business Process Model Process Instance 
These 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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alireza Rezaei Mahdiraji
    • 1
  • Bruno Rossi
    • 1
  • Alberto Sillitti
    • 1
  • Giancarlo Succi
    • 1
  1. 1.Center for Applied Software Engineering (CASE)Free University of Bozen-BolzanoBolzanoItaly

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