Profiling event logs to configure risk indicators for process delays

A. Pika, W.M.P. Aalst, van der, C.J. Fidge, A.H.M. Hofstede, ter, M.T. Wynn

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureHoofdstukAcademic

18 Citaten (Scopus)

Samenvatting

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.
Originele taal-2Engels
TitelAdvanced Information Systems Engineering (25th International Conference, CAiSE 2013, Valencia, Spain, June 17-21, 2013. Proceedings)
RedacteurenC. Salinesi, M.C. Norrie, O. Pastor
Plaats van productieBerlin
UitgeverijSpringer
Pagina's465-481
ISBN van geprinte versie978-3-642-38708-1
DOI's
StatusGepubliceerd - 2013

Publicatie series

NaamLecture Notes in Computer Science
Volume7908

Vingerafdruk

Duik in de onderzoeksthema's van 'Profiling event logs to configure risk indicators for process delays'. Samen vormen ze een unieke vingerafdruk.

Citeer dit