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Decomposable algorithms for nearest neighbor computing

机译:最近邻计算的可分解算法

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摘要

Privacy and security concerns can prevent sharing of data, derailing many data projects. Distributed knowledge computing, if done correctly, can alleviate this problem. The key is to obtain valid results, while providing guarantees on the (non)disclosure of data. In the present study, two novel algorithms have been developed to find the nearest neighbor from known points, and a pair of nearest neighbors in a given set data points in d-dimensional space in distributed databases. These algorithms preserve the privacy and security of the data at individual sites by requiring transmission of only minimal information to other sites.
机译:隐私和安全问题会阻止数据共享,从而使许多数据项目脱轨。如果正确完成了分布式知识计算,则可以缓解此问题。关键是要获得有效的结果,同时要保证(不)公开数据。在本研究中,已经开发了两种新颖的算法来从已知点中找到最近的邻居,以及在分布式数据库中d维空间中给定集合数据点中的一对最近的邻居。这些算法通过只需要向其他站点传输最少的信息来保护各个站点的数据的隐私和安全性。

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