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Instant Social Graph Search

机译:即时社交图搜索

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摘要

In this paper, we study a new problem of instant social graph search, which aims to find a sub graph that closely connects two and more persons in a social network. This is a natural requirement in our real daily life, such as "Who can be my referrals for applying for a job position?". In this paper, we formally define the problem and present a series of approximate algorithms to solve this problem: Path, Influence, and Diversity. To evaluate the social graph search results, we have developed two prototype systems, which are online available and have attracted thousands of users. In terms of both user's viewing time and the number of user clicks, we demonstrate that the three algorithms can significantly outperform (+34.56%-+131.37%) the baseline algorithm.
机译:在本文中,我们研究了即时社交图搜索的新问题,该问题旨在找到一个将社交网络中的两个或更多人紧密联系在一起的子图。这是我们现实生活中的自然要求,例如“谁可以成为我申请工作职位的推荐人?”。在本文中,我们正式定义了问题,并提出了一系列解决该问题的近似算法:路径,影响和多样性。为了评估社交图搜索结果,我们开发了两个原型系统,这些系统可以在线使用并吸引了成千上万的用户。就用户的观看时间和用户点击次数而言,我们证明了这三种算法可以明显优于基准算法(+34.56%-+ 131.37%)。

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