teis_a_1402371_sm9188.pdf (268.88 kB)
A systematic mapping study of process mining
Version 2 2017-11-25, 05:28
Version 1 2017-11-21, 02:53
journal contribution
posted on 2017-11-25, 05:28 authored by Ana Rocío Cárdenas Maita, Lucas Corrêa Martins, Carlos Ramón López Paz, Laura Rafferty, Patrick C. K. Hung, Sarajane Marques Peres, Marcelo FantinatoThis 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.