A Hybrid Approach for Process Mining: Using From-to Chart Arranged by Genetic Algorithms

Esgin E., Senkul P., Cimenbicer C.

5th International Conference on Hybrid Artificial Intelligence Systems, San Sebastian, Spain, 23 - 25 June 2010, vol.6076, pp.178-180, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 6076
  • City: San Sebastian
  • Country: Spain
  • Page Numbers: pp.178-180
  • Keywords: From-to Chart, Genetic Algorithms (GA), Process Mining, Business Process Modeling (BPM), Event Logs, PROCESS MODELS, LOGS
  • Middle East Technical University Affiliated: Yes

Abstract

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.