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A Framework to Evaluate and Compare Decision-Mining Techniques

  • Toon JouckEmail author
  • Massimiliano de Leoni
  • Benoît Depaire
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 342)

Abstract

During the last decade several decision mining techniques have been developed to discover the decision perspective of a process from an event log. The increasing number of decision mining techniques raises the importance of evaluating the quality of the discovered decision models and/or decision logic. Currently, the evaluations are limited because of the small amount of available event logs with decision information. To alleviate this limitation, this paper introduces the ‘DataExtend’ technique that allows evaluating and comparing decision-mining techniques with each other, using a sufficient number of event logs and process models to generate evaluation results that are statistically significant. This paper also reports on an initial evaluation using ‘DataExtend’ that involves two techniques to discover decisions, whose results illustrate that the approach can serve the purpose.

Keywords

Decision mining Evaluation Log generation 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Toon Jouck
    • 1
    Email author
  • Massimiliano de Leoni
    • 2
  • Benoît Depaire
    • 1
  1. 1.UHasselt - Hasselt UniversityHasseltBelgium
  2. 2.Eindhoven University of TechnologyEindhovenThe Netherlands

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