Information extraction for business process modeling Research topic:Business process modeling

  • Type:Masterarbeit
  • Supervisor:

    Schüler, Selina
     

Further information

In business process management, the documentation of business processes is still predominantly carried out manually in a time-consuming and error-prone manner. However, there are already some approaches for improving process recording and process modeling through automation. One possibility is to generate a Petri net from XML-based documents. With higher Petri nets (e.g. Pr/T net), switching conditions can be further specified on the basis of more distinguishable markers. For example, if a marker in the "new invoice" position represents a specific invoice and the position is followed by a "grant discount" transition, it can be specified in the transition that only invoices over €500 should receive a discount. In this assignment, you will therefore develop a concept for how these business rules can be suggested to the modeler based on the documents. For example, the documents must be compared with each other and the cases in which a document only occurs must be checked. In the thesis, you will look at different approaches in order to subsequently develop a concept and implement it as a prototype. Language models, for example, could be used to extract information. However, since semi-structured data is assumed, non-NLP-based methods could also be used.


Please apply under the following link: https://portal.wiwi.kit.edu/forms/form/Bewerbung_Abschlussarbeit_AIFB-BIS