A Semantics-Based Privacy-Aware Approach for Fragmenting Business Processes

There is a growing need for the ability to fragment ones business processes effectively, in order to get useful fragments for future reutilization in building business processes. This can prove to increase the productivity and shorten the development time. The decomposition task aims at clustering workflow activities into fragments according to business constraints. Existing approaches lack semantic and privacy concerns. In this paper, we propose a semantic fragment identification approach to assemble activities that are semantically close according a semantic attraction threshold. Moreover, Fragments must be aware of sensitive information preserving. Our fragmentation approach is based on the so-called formal concept analysis approach, while integrating a semantic clustering technique for avoiding the association of sensitive information.