Who Is Behind the Model? Classifying Modelers Based on Pragmatic Model Features View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-08-11

AUTHORS

Andrea Burattin , Pnina Soffer , Dirk Fahland , Jan Mendling , Hajo A. Reijers , Irene Vanderfeesten , Matthias Weidlich , Barbara Weber

ABSTRACT

Process modeling tools typically aid end users in generic, non-personalized ways. However, it is well conceivable that different types of end users may profit from different types of modeling support. In this paper, we propose an approach based on machine learning that is able to classify modelers regarding their expertise while they are creating a process model. To do so, it takes into account pragmatic features of the model under development. The proposed approach is fully automatic, unobtrusive, tool independent, and based on objective measures. An evaluation based on two data sets resulted in a prediction performance of around 90%. Our results further show that all features can be efficiently calculated, which makes the approach applicable to online settings like adaptive modeling environments. In this way, this work contributes to improving the performance of process modelers. More... »

PAGES

322-338

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-98648-7_19

DOI

http://dx.doi.org/10.1007/978-3-319-98648-7_19

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106097232


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