CONDA-PM—A Systematic Review and Framework for Concept Drift Analysis in Process Mining

Author:

Elkhawaga GhadaORCID,Abuelkheir MervatORCID,Barakat Sherif I.ORCID,Riad Alaa M.ORCID,Reichert ManfredORCID

Abstract

Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts.

Funder

Mansoura University

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Reference55 articles.

1. Process mining manifesto;van der Aalst,2012

2. Process Mining: Data Science in Action;van der Aalst,2016

3. Process histories-detecting and representing concept drifts based on event streams;Stertz,2018

4. Finding process variants in event logs;Bolt,2017

5. Detecting deviating behaviors without models;Lu,2016

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