Abstract
Modern enterprises are increasingly moving towards the workflow paradigm in modeling their business process. One prevailing approach counts on process mining that aims to discover workflow models from log files which contain rich process information. The process models discovered are then used to model and design information systems intended for workflow management. Although workflow logs contain rich information, they have not been made full use in many existing modeling formalisms like Petri nets. In this paper, we propose a novel approach for process mining using event graph to integrate various process related information. Analysis is conducted to show the advantages of event graph based models compared to Petri nets. A case study is also reported to illustrate the entire mining process. Finally, a preliminary evaluation is conducted to show the merits of our method in terms of precision, generalization and robustness.
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Zhang, H., Liu, Y., Li, C., Jiao, R. (2010). A Novel Approach of Process Mining with Event Graph. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15387-7_17
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DOI: https://doi.org/10.1007/978-3-642-15387-7_17
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