A new approach for maximizing bichromatic reverse nearest neighbor search
A new approach for maximizing bichromatic reverse nearest neighbor search
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DOI：
10.1007/s10115-012-0527-4
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发表时间：
2013-07
影响因子：
2.7
通讯作者：
Yubao Liu;R. C. Wong;Ke Wang;Zhijie Li;Cheng Chen;Zitong Chen
中科院分区：
文献类型：
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作者：
Yubao Liu;R. C. Wong;Ke Wang;Zhijie Li;Cheng Chen;Zitong Chen
最大化双色反向最近邻（MaxBRNN）是双色反向最近邻（BRNN）的一个变体。MaxBRNN问题的目的是找到一个最佳区域，使BRNN的大小最大化。该问题在选址规划和基于客户资料的营销等领域有着广泛的真实的应用。MaxBRNN问题最著名的算法叫做MaxOverlap。在本文中，我们研究了MaxBRNN问题，并提出了一种新的方法称为MaxSegment的二维空间时，使用的范数。然后，我们将我们的算法扩展到MaxBRNN问题的其他变体，例如MaxBRNN问题与其他度量空间和三维空间。最后，我们在真实的数据集和人工数据集上进行了实验，并与现有算法进行了比较。实验结果验证了该方法的有效性。
Maximizing bichromatic reverse nearest neighbor (MaxBRNN) is a variant of bichromatic reverse nearest neighbor (BRNN). The purpose of the MaxBRNN problem is to find an optimal region that maximizes the size of BRNNs. This problem has lots of real applications such as location planning and profile-based marketing. The best-known algorithm for the MaxBRNN problem is calledMaxOverlap. In this paper, we study the MaxBRNN problem and propose a new approach calledMaxSegmentfor a two-dimensional space when the-norm is used. Then, we extend our algorithm to other variations of the MaxBRNN problem such as the MaxBRNN problem with other metric spaces, and a three-dimensional space. Finally, we conducted experiments on real and synthetic datasets to compare our proposed algorithm with existing algorithms. The experimental results verify the efficiency of our proposed approach.