Gesellschaft für Informatik e.V.

Lecture Notes in Informatics


Enterprise modelling and information systems architectures - EMISA 2014 P-234, 71-84 (2014).

Gesellschaft für Informatik, Bonn
2014


Copyright © Gesellschaft für Informatik, Bonn

Contents

Designing and implementing a framework for event-based predictive modelling of business processes

Jörg Becker , Dominic Breuker , Patrick Delfmann and Martin Matzner

Abstract


Applying predictive modelling techniques to event data collected during business process execution is receiving increasing attention in the literature. In this paper, we present a framework supporting real-time prediction for business processes. After fitting a probabilistic model to historical event data, the framework can predict how running process instances will behave in the near future, based on the behaviour seen so far. The probabilistic modelling approach is carefully designed to deliver comprehensible results that can be visualized. Thus, domain experts can judge the predictive models by comparing the visualizations to their experience. Model analysis techniques can be applied if visualizations are too complex to be understood entirely. We evaluate the framework's predictive modelling component on real-world data and demonstrate how the visualization and analysis techniques can be applied.


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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-628-2


Last changed 31.10.2014 16:53:48