Semantic and structural performer clustering in BPMN models transformed into social network models

Current trends in organization restructuring focus on the social relationships among the organizational actors in order to improve the business process. Proposed business process model restructuring approaches adopt either social network discovery or rediscovery techniques. Social network discovery uses semantic information to guide the affiliation process during its analyses, whereas social network rediscovery uses structural information to identify groups in the social network. In this paper, we propose a hybrid method that exploits both knowledge discovery and rediscovery to suggest a new structure of a business process model that is based on performers clustering. Using the context concept, the proposed method applies a hierarchical clustering algorithm to determine the performer partitions; the algorithm uses two newly defined distances that account for the semantic and structural information. The method is illustrated and evaluated experimentally to analyze its performance.