Joint search by social and spatial proximity
Joint search by social and spatial proximity
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DOI：
10.1109/icde.2016.7498434
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发表时间：
2016-05
期刊：
影响因子：
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通讯作者：
K. Mouratidis;Jing Li;Yu Tang;N. Mamoulis
中科院分区：
文献类型：
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作者：
K. Mouratidis;Jing Li;Yu Tang;N. Mamoulis
社交网络的扩散为高级服务带来了新的挑战和机遇，尤其是随着它们不断增加基于位置的特征。我们展示了如何将社会和空间接近的应用程序，如公司和朋友推荐可以显着受益，并研究了查询类型，捕捉这些双重语义。我们开发了高度可扩展的算法来处理它，并使用真实的社交网络数据来实证验证它们的效率和功效。
The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and use real social network data to empirically verify their efficiency and efficacy.