Andrea Burattin

Associate Professor
Technical University of Denmark


Who is behind the Model? Classifying Modelers based on Pragmatic Model Features

A. Burattin, P. Soffer, D. Fahland, J. Mendling, H.A. Reijers, I. Vanderfeesten, M. Weidlich, B. Weber
Abstract
Paper cover

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.

Paper Information and Files

In Proceedings of BPM 2018; Sydney, Australia; September 2018.

Presentation Slides
General rights

Copyright and moral rights for the publications made accessible in the public website are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Latest website update: 17 April 2024.