计算机科学 ›› 2012, Vol. 39 ›› Issue (11): 131-136.

• 数据库与数据挖掘 • 上一篇    下一篇

路网中双色数据集上连续反向k近邻查询处理的研究

李艳红 李国徽 杜小坤   

  1. (中南民族大学计算机科学学院 武汉 430074) (华中科技大学计算机科学与技术学院 武汉 430074)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Study on Continuous Bichromatic Reverse k Nearest Neighbor Query Processing in Road Networks

  • Online:2018-11-16 Published:2018-11-16

摘要: 近年来,反向最近邻查询(RNN)算法研究得到了普遍的关注,成为了数据库领域的一个研究热点。欧氏空 间中提出了较多的高效算法,而路网中的反向最近邻处理方面所做的工作不够,有关这方面的成果较少。路网中查询 点和数据对象之间以及不同数据对象之间的距离受到路网连通性的影响,欧氏空间中的反向最近部方法在路网中不 适用。反向最近部查询有两种类型:单色反向最近部查询(Monochromatic RNN, MRNN)和双色反向最近部查询(13i- chromatic RNN,13RNN)。到目前为止,仍然没有有效的算法来处理路网中双色数据集上的连续反向k近部查询。因 此,研究路网中双色数据集上连续反向k近部查询是很有意义的。

关键词: 反向最近部查询,路网,双色数据集,连续监控

Abstract: In recent years,reverse nearest neighbor (RNN) query processing has received wide concern and has become a hot research topic in the database field. Many efficient RNN query processing methods in Euclidean spaces have been proposed. However, there is few related research findings in road networks. RNN processing methods in Euclidean spaces arc unsuitable for RNN processing in road networks where the query-object distance and object object distance arc determined by the connectivity of the road network. RNN query can be roughly classified into two types:Monochro- matic RNN(MRNN) query and 13ichromatic RNN(13RNN) query. Up to now, there is still a lack of efficient algorithms for processing continuous bichromatic reverse k nearest neighbor (CI3RkNN) queries in road networks. Thus, it is es- sential to examine CBRkNN queries in road networks and present efficient methods for CBRkNN query processing in road networks.

Key words: Reverse nearest neighbor query, Road network, I3ichromatic data set, Continuous monitoring

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