论文标题
N维k-vector及其在正交范围搜索中的应用
The n-dimensional k-vector and its application to orthogonal range searching
论文作者
论文摘要
这项工作着重于n维k-vector的定义和研究，该算法设计用于在具有多个维度的静态数据库中执行正交范围搜索。该方法首先找到搜索维度的顺序，然后使用修改后的投影方法执行搜索。为了确定尺寸顺序，该算法使用k-vector，这是一种范围搜索技术，可确定搜索范围内包含的元素数量。然后，使用此信息，该算法可以预测并选择处理每个维度的最佳方法。该算法具有$ \ MATHCAL {o}（nd（k/n）^{2/d}）$的最坏情况，其中$ k $是检索到的元素的数量，$ n $是数据库中的元素数量，$ d $是$ d $是数据库尺寸的数量。这项工作包括对方法的详细描述以及对算法性能的研究。
This work focuses on the definition and study of the n-dimensional k-vector, an algorithm devised to perform orthogonal range searching in static databases with multiple dimensions. The methodology first finds the order in which to search the dimensions, and then, performs the search using a modified projection method. In order to determine the dimension order, the algorithm uses the k-vector, a range searching technique for one dimension that identifies the number of elements contained in the searching range. Then, using this information, the algorithm predicts and selects the best approach to deal with each dimension. The algorithm has a worst case complexity of $\mathcal{O}(nd(k/n)^{2/d})$, where $k$ is the number of elements retrieved, $n$ is the number of elements in the database, and $d$ is the number of dimensions of the database. This work includes a detailed description of the methodology as well as a study of the algorithm performance.
