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From Semantically Abstracted Traces to Process Mining and Process Model Comparison

  • Giorgio Leonardi
  • Manuel Striani
  • Silvana Quaglini
  • Anna Cavallini
  • Stefania MontaniEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11298)

Abstract

Process model comparison can be exploited to assess the quality of organizational procedures, to identify non-conformances with respect to given standards, and to highlight critical situations. Sometimes, however, it is difficult to make sense of large and complex process models, while a more abstract view of the process would be sufficient for the comparison task. In this paper, we show how process traces, abstracted on the basis of domain knowledge, can be provided as an input to process mining, and how abstract models (i.e., models mined from abstracted traces) can then be compared and ranked, by adopting a similarity metric able to take into account penalties collected during the abstraction phase. The overall framework has been tested in the field of stroke management, where we were able to rank abstract process models more similarly to the ordering provided by a domain expert, with respect to what could be obtained when working on non-abstract ones.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Giorgio Leonardi
    • 1
  • Manuel Striani
    • 2
  • Silvana Quaglini
    • 3
  • Anna Cavallini
    • 4
  • Stefania Montani
    • 1
    Email author
  1. 1.DISIT, Computer Science InstituteUniversity of Piemonte OrientaleAlessandriaItaly
  2. 2.Department of Computer ScienceUniversity of TorinoTurinItaly
  3. 3.Department of Electrical, Computer and Biomedical EngineeringUniversity of PaviaPaviaItaly
  4. 4.Istituto di Ricovero e Cura a Carattere Scientifico Fondazione “C. Mondino” - on behalf of the Stroke Unit Network (SUN) Collaborating CentersPaviaItaly

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