A Hybrid Approach for Process Mining Using From to Chart Arranged by Genetic Algorithms LNCS San Sebastian Spain June 2010

Esgin, Eren
Karagöz, Pınar
In the scope of this study, a hybrid data analysis methodology to business process modeling is proposed in such a way that; From-to Chart, which is basically used as the front-end to figure out the observed patterns among the activities at realistic event logs, is rearranged by Genetic Algorithms to convert these derived raw relations into activity sequence. According to experimental results, acceptably good (sub-optimal or optimal) solutions are obtained for relatively complex business processes at a reasonable processing time period.