Discovering the most potential stars in social networks with infra-skyline queries

With the rapid development of Social Network (SN for short), people increasingly pay attention to the importance of the roles which they play in the SNs. As is usually the case, the standard for measuring the importance of the members is multi-objective. The skyline operator is thus introduced to distinguish the important members from the entire community. For decision-making, people are interested in the most potential members which can be promoted into the skyline with minimum cost, namely the problem of Member Promotion in Social Networks. In this paper, we propose some interesting new concepts such as Infra-Skyline and Promotion Boundary, and then we exploit a novel promotion boundary based approach, i.e., the InfraSky algorithm. Extensive experiments on both real and synthetic datasets are conducted to show the effectiveness and efficiency of the InfraSky algorithm.