Conference Proceedings

Predictive Process Monitoring in Apromore

I Verenich, S Mõškovski, S Raboczi, M Dumas, M La Rosa, FM Maggi

Lecture Notes in Business Information Processing | Springer-Verlag, Journals | Published : 2018

Abstract

This paper discusses the integration of Nirdizati, a tool for predictive process monitoring, into the Web-based process analytics platform Apromore. Through this integration, Apromore’s users can use event logs stored in the Apromore repository to train a range of predictive models, and later use the trained models to predict various performance indicators of running process cases from a live event stream. For example, one can predict the remaining time or the next events until case completion, the case outcome, or the violation of compliance rules or internal policies. The predictions can be presented graphically via a dashboard that offers multiple visualization options, including a range ..

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Grants

Awarded by Australian Research Council


Awarded by Estonian Research Council