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 language | English |
|---|---|
| Pages (from-to) | 505-549 |
| Number of pages | 45 |
| Journal | Enterprise Information Systems |
| Volume | 12 |
| Issue number | 5 |
| DOIs | |
| State | Published - 28 May 2018 |
| Externally published | Yes |
Keywords
- Data mining
- business process management
- computational intelligence
- machine learning
- process mining
- systematic review
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