• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

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利用离散边界点判断的反向最远邻查询算法

杨秀娟1,宋俊山2,董军1,王丽芬1   

  1. (1.黑龙江科技大学计算机与信息工程学院,黑龙江 哈尔滨 150022;2.大庆金桥信息技术工程有限公司,黑龙江 大庆 163311)
  • 收稿日期:2015-03-20 修回日期:2015-08-19 出版日期:2016-08-25 发布日期:2016-08-25
  • 基金资助:

    黑龙江省教育厅科学技术研究项目(12541731)

A reverse furthest neighbor query algorithm using discrete boundary points for judgment            

YANG Xiu-juan1,SONG Jun-shan2,DONG Jun1,WANG Li-fen1   

  1. (1.College of Computer and Information Engineering,Heilongjiang University of Science and Technology,Harbin 150022;
    2.Daqing Sunbridge Information Technology Engineering Co.,Ltd.,Daqing 163311,China)
  • Received:2015-03-20 Revised:2015-08-19 Online:2016-08-25 Published:2016-08-25

摘要:

目前大部分的反向最远邻查询方法对查询点是否存在反向最远邻的情况不进行判断,当查询点不存在反向最远邻的结果集时,也进行全部的操作,增加了查询消耗。针对这种情况,提出了利用离散边界点判断查询点是否存在反向最远邻结果集的方法,利用离散边界点、四分邻域区和半平面修剪策略进行过滤操作,并验证过滤后得到的结果集中数据点的有效性。实验测试了查询点的位置对查询的影响和数据集的大小以及数据分布对查询的影响,并与利用凸包判断的方法进行了对比分析。实验结果表明,当查询点不是离散边界点时,查询消耗几乎为0,当查询点移动到边界时,查询消耗增加。实验表明提出的方法可以得到查询点的反向最远邻结果集。

关键词: 空间数据库, 反向最远邻查询, 离散边界点, 半平面修剪策略, 四分邻域区

Abstract:

At present, most of reverse furthest neighbor (RFN) query methods do not judge whether the query point has a result set, so even when a RFN result set does not exist, all the operations are still done and time is vainly consumed. To effectively deal with the RFN query problems, we propose a method in which whether the query point having a RFN result set is judged by discrete boundary points. Discrete boundary points, four neighborhood areas and half space trimming strategy are employed to do the filtering, and then the result set obtained by the filtering is verified. The impact of the position of the query point, the size of data sets and data distribution on queries is tested, which is also compared with that of the judging method using convex. Experimental results show that when the query point is not a discrete boundary point, the time consumption for queries is almost zero; but when the query point is a discrete boundary point, the time consumption increases, which demonstrates that the proposed method is effective and can get the RFN results set.

Key words: spatial database, reverse furthest neighbors query, discrete boundary points, half-space trimming strategy, four neighborhood areas