BORDER: Efficient computation of boundary points
BORDER: Efficient computation of boundary points
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DOI：
10.1109/tkde.2006.38
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发表时间：
2006-03-01
影响因子：
8.9
通讯作者：
Ooi, BC
中科院分区：
文献类型：
--
作者：
Xia, CY;Hsu, W;Ooi, BC
这项工作解决了在多维数据集中寻找边界点的问题。边界点是位于密集分布的数据(如集群)边缘的数据点。我们描述了一种新的方法，称为边界(边界点检测器)来检测这些点。BORDER使用了最先进的数据库技术-GORDER KNN连接，并利用了反向k近邻(RkNN)的特殊性质。在具有不同特征的数据集上的实验研究表明，边界能够有效和高效地检测出边界点。
This work addresses the problem of finding boundary points in multidimensional data sets. Boundary points are data points that are located at the margin of densely distributed data such as a cluster. We describe a novel approach called BORDER ( a BOundaRy points DEtectoR) to detect such points. BORDER employs the state-of-the-art database technique - the Gorder kNN join and makes use of the special property of the reverse k nearest neighbor (RkNN). Experimental studies on data sets with varying characteristics indicate that BORDER is able to detect the boundary points effectively and efficiently.