Abstract : The manual construction of business process models is a time-consuming and error-prone task. To ease the construction of such models, several modeling support techniques have been suggested. However, while recommendation systems are widely used e.g. in e-commerce, such techniques are rarely implemented in process modeling tools. The creation of such systems is a complex task since a large number of requirements and parameters have to be addressed. In order to improve the situation, we develop a data model that can serve as a backbone for the development of process modeling recommender systems (PMRS). We systematically develop the model in a stepwise approach using established requirements and validate it against a data model that has been reverse-engineered from a real-world system. We expect that our contribution will provide a useful starting point for designing the data perspective of process modeling recommendation features.
https://hal.inria.fr/hal-01653517 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Friday, December 1, 2017 - 3:15:20 PM Last modification on : Friday, August 5, 2022 - 2:33:52 PM
Michael Fellmann, Dirk Metzger, Oliver Thomas. Data Model Development for Process Modeling Recommender Systems. 9th IFIP Working Conference on The Practice of Enterprise Modeling (PoEM), Nov 2016, Skövde, Sweden. pp.87-101, ⟨10.1007/978-3-319-48393-1_7⟩. ⟨hal-01653517⟩