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A systematic mapping study of process mining

  • Ana Rocío Cárdenas Maita
  • , Lucas Corrêa Martins
  • , Carlos Ramón López Paz
  • , Laura Rafferty
  • , Patrick C.K. Hung
  • , Sarajane Marques Peres
  • , Marcelo Fantinato

Research output: Contribution to journal › Review article › peer-review

56 Scopus citations

Abstract

This study systematically assesses the process mining scenario from 2005 to 2014. The analysis of 705 papers evidenced ‘discovery’ (71%) as the main type of process mining addressed and ‘categorical prediction’ (25%) as the main mining task solved. The most applied traditional technique is the ‘graph structure-based’ ones (38%). Specifically concerning computational intelligence and machine learning techniques, we concluded that little relevance has been given to them. The most applied are ‘evolutionary computation’ (9%) and ‘decision tree’ (6%), respectively. Process mining challenges, such as balancing among robustness, simplicity, accuracy and generalization, could benefit from a larger use of such techniques.

Original languageEnglish
Pages (from-to)505-549
Number of pages45
JournalEnterprise Information Systems
Volume12
Issue number5
DOIs
StatePublished - 28 May 2018
Externally publishedYes

Keywords

  • Data mining
  • business process management
  • computational intelligence
  • machine learning
  • process mining
  • systematic review

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