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.
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Esgin, E., Senkul, P., Cimenbicer, C. (2010). A Hybrid Approach for Process Mining: Using From-to Chart Arranged by Genetic Algorithms. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13769-3_22
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DOI: https://doi.org/10.1007/978-3-642-13769-3_22
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