A Role-Based Semantic Framework for Collaborative Socialized Process Model Reconstruction

Collaborative socialized process model reconstruction plays important roles in social network management. Group multi-role identification aims to the optimal collaboration performance by assigning potential roles to candidates. It could improve social process services management. In this work, we pay a specific attention to the challenge of the lack of formalization to describe human resources in business process. Based on Social Network Analysis (SNA), a semantic framework provides semantic description of human resources for social business process reconstruction. The main contributions of this paper includes: (1) By formalizing the semantic collaborative social process model for collaborative task assignment, a role-based semantic framework for Social Process Modeling Ontology (SPMO) is proposed; (2) A series of computational solutions for measuring multi-group collaboration performance and interaction cost are proposed for combinatorial optimization problem; and (3) two algorithms, SSPGC (semantic social process graph construction) and CSNRC (collaborative socialized network reconstruction) are proposed for semantic analysis on collaborative social process models. Finally, the experimental results show that our solution is a scalable framework and can be efficiently applied in reconstructing collaborative process model in real-world networks and obtaining optimal performance.