Social network has emerged as an important paradigm in modern business operation.Outsourcing tasks to social network helps organizations to mitigate the shortage of skill or expertise in some domain.Expert team discovery is an important problem in complex collaborative networks.Current expert team discovery models are need to traverse every candidate in expert network until optimal team scheme is found,which would generate massive computational costs.In this paper,a team formation model is proposed to outsource tasks to social networks.In order to reduce searching space of team formation for seeded candidates,the proposed model selects centrality expert list as seeds to obtain a lower communication cost.Moreover,based on the notion of Skyline,the proposed model can effectively and efficiently identify experts by reducing the number of expert candidates.Theoretical analysis and extensive experiments on real and synthetically generated dataset demonstrate the effectiveness and scalability of the proposed method.