Discovering the Most Potential Stars in Social Networks with Infra-skyline Queries
Discovering the Most Potential Stars in Social Networks with Infra-skyline Queries
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DOI：
10.1007/978-3-642-29253-8_12
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发表时间：
2012-04
期刊：
影响因子：
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通讯作者：
Zhuo Peng;Chaokun Wang;Lu Han;Jingchao Hao;Xiaoping Ou
中科院分区：
文献类型：
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作者：
Zhuo Peng;Chaokun Wang;Lu Han;Jingchao Hao;Xiaoping Ou
随着社会网络的迅速发展，人们越来越关注自己在社会网络中所扮演的角色的重要性。通常情况下，衡量成员重要性的标准是多目标的。因此，引入天际线操作符来区分整个社区的重要成员。在决策中，人们关注的是以最小的代价将最有潜力的成员提升到天际线，即社交网络中的成员提升问题。在本文中，我们提出了一些有趣的新概念，如天空轮廓和提升边界，然后我们开发了一种新的基于提升边界的方法，即，天空算法。在真实的数据集和人工合成数据集上进行了大量的实验，以证明该算法的有效性和效率。
With the rapid development ofSocial 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 ofMember Promotion in Social Networks. In this paper, we propose some interesting new concepts such asInfra-SkylineandPromotion 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.