• DocumentCode
    3640962
  • Title

    A framework for comparing process mining algorithms

  • Author

    Philip Weber;Behzad Bordbar;Peter Tiňo;Basim Majeed

  • Author_Institution
    School of Computer Science University of Birmingham, B15 2TT, UK
  • fYear
    2011
  • Firstpage
    625
  • Lastpage
    628
  • Abstract
    There are many process mining algorithms with different theoretical foundations and aims, raising the question of how to choose the best for a particular situation. A framework is proposed for objectively comparing algorithms for process discovery against a known ground truth, with an implementation using existing tools. Results from an experimental evaluation of five algorithms against basic process structures confirm the validity of the approach. In general, numbers of traces for mining are predictable from the structure and probabilities in the model, but there are some algorithm-specific differences.
  • Keywords
    "Data mining","Business","PROM","Prediction algorithms","Algorithm design and analysis","Data models","Predictive models"
  • Publisher
    ieee
  • Conference_Titel
    GCC Conference and Exhibition (GCC), 2011 IEEE
  • Print_ISBN
    978-1-61284-118-2
  • Type

    conf

  • DOI
    10.1109/IEEEGCC.2011.5752616
  • Filename
    5752616