Application of Bayesian Networks to Recommendations in Business Process Modeling

Formalized process models help to handle, design and store processes in a form understandable for the designers and users. Modeling of business processes is a complex task, which can be supported by recommendations. It is important, as designers prefer to receive and use suggestions during the modeling process. Recommendations make modeling faster and less error-prone because a set of good models is automatically used to help the designer. In this paper, we propose a method that uses Bayesian Networks for recommendation purposes in process modeling. To create such a network, we use configurable business processes that combine a set of reference models.

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