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A new K-NN query algorithm based on the dynamic movement of spatial objects

机译:基于空间物体动态运动的K-NN查询新算法

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The K-NN query algorithm is an important class of query algorithm in spatial database, the traditional K-NN query algorithm used the measurement distance and pruning strategy to search in the adopted index tree, the regional division algorithm based on the grid obtained the nearest neighbor objects by calculating the distance between the queried object and the data objects within the eight grids around the queried object, and carried on expanding inquiry scope outward layer by layer, in view of the advantage of the grid index, a new K-NN query algorithm based on the dynamic movement of spatial objects is proposed in this paper, it only carries on grid division to a small part of region around the queried object, when all the data objects in the current grid are already searched, make the cells in the grid empty, dynamically move the external data objects into the grid area continue to query according to the relative position of these objects, because the algorithm uses a fixed grid area to query the data objects in the whole region, so it can reduce the target storage space and the complexity degree of the algorithm calculation, the experiments show that the new query algorithm is superior to the traditional algorithms in the querying performance when the amount of data is increased, and the query efficiency is greatly increased.
机译:K-NN查询算法是空间数据库中一类重要的查询算法,传统的K-NN查询算法采用测量距离和修剪策略在采用的索引树中进行搜索,基于网格的区域划分算法获得了最近的通过计算被查询对象与被查询对象周围八个网格内数据对象之间的距离,计算相邻对象,并利用网格索引的优势,逐层向外扩展查询范围,提出了一种新的K-NN查询方法本文提出了一种基于空间对象动态运动的算法,它只对被查询对象周围的一小部分区域进行网格划分,当当前网格中的所有数据对象已被搜索完毕时,使网格中的单元成为可能。网格为空,将外部数据对象动态移动到网格区域中,继续根据这些对象的相对位置进行查询,因为该算法使用的是固定网格通过查询整个区域的数据对象,可以减少目标存储空间和算法计算的复杂程度,实验表明,新查询算法在查询量较大时,其查询性能优于传统算法。数据增加,查询效率大大提高。

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