Profiling event logs to configure risk indicators for process delays
Pika, Anastasiia, van der Aalst, Wil M.P., Fidge, Colin J., ter Hofstede, Arthur H.M., & Wynn, Moe T. (2013) Profiling event logs to configure risk indicators for process delays. In Advanced Information Systems Engineering (CAISE 2013), Springer, Valencia, Spain, pp. 465-481.
Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.
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|Item Type:||Conference Paper|
|Keywords:||process risk indicators, process mining, risk identification|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
|Divisions:||Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2013 Springer-Verlag Berlin Heidelberg|
|Deposited On:||08 Jul 2013 22:58|
|Last Modified:||11 Jul 2013 07:14|
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