Skyline queries are important in many application domains. In this paper, we propose a novel structure Skyline Diagram, which given a set of points, partitions the plane into a set of regions, referred to as skyline polyominos. All query points in the same skyline polyomino have the same skyline query results. Similar to $k$kth-order Voronoi diagram commonly used to facilitate $k$k nearest neighbor ($k$kNN) queries, skyline diagram can be used to facilitate skyline queries and many other applications. However, it may be computationally expensive to build the skyline diagram. By exploiting some interesting properties of skyline, we present several efficient algorithms for building the diagram with respect to three kinds of skyline queries, quadrant, global, and dynamic skylines. In addition, we propose an approximate skyline diagram which can significantly reduce the space cost. Experimental results on both real and synthetic datasets show that our algorithms are efficient and scalable.

中文翻译：

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天际线图：天际线查询的高效空间分区

Skyline 查询在许多应用程序领域中都很重要。在本文中，我们提出了一种新颖的结构天际线图，给定一组点，将平面划分为一组区域，称为天际线多米诺骨牌。同一个 Skyline polyomino 中的所有查询点都具有相同的 Skyline 查询结果。如同$千$克三阶 Voronoi 图 通常用于方便 $千$克 最近的邻居 （$千$克NN) 查询，天际线图可用于方便天际线查询和许多其他应用。然而，构建天际线图在计算上可能很昂贵。通过利用天际线的一些有趣特性，我们提出了几种有效的算法来构建关于三种天际线查询（象限、全局和动态天际线）的图表。此外，我们提出了一个近似的天际线图，可以显着降低空间成本。在真实数据集和合成数据集上的实验结果表明，我们的算法高效且可扩展。