J4

• 计算机科学 • 上一篇    下一篇

一种改进R-Link的空间数据检索算法

赵 伟1,2, 李文辉1, 张 姝2   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012; 2. 长春工业大学 计算机科学与工程学院, 长春 130012
  • 收稿日期:2007-07-20 修回日期:1900-01-01 出版日期:2008-05-26 发布日期:2008-05-26
  • 通讯作者: 李文辉

An Improved R-Link Spatial Data Index Algorithm

ZHAO Wei1,2, LI Wenhui1, ZHANG Shu2   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. School of Computer Science & Engineering, Changchun University of Technology, Changchun 130012, China
  • Received:2007-07-20 Revised:1900-01-01 Online:2008-05-26 Published:2008-05-26
  • Contact: LI Wenhui

摘要: 提出一种基于R-Link树的快速空间索引结构, 并在该结构中引入K-Means算法. 在K-Means算法中采用均值标准差确定初始聚类中心, 提高了收敛速度, 并通过距离准则函数优化K值, 避免了K值的盲目选取. 与R-Link相比空间开销代价稍大, 但性能更高, 且数据量越多, 此结构的整体性能越好.

关键词: 空间数据库, R-Link树, 四叉树, 空间聚类, 空间索引

Abstract: This paper presents a quick speed spatial indexing structure which is based on R-link tree. And we introduced K-Means algorithm into the structure. In K-Means algorithm, we adopted valuestandard deviation to ascertain the initial clustering centres to improve convergence speed and we ascertained ultimate K value by distance criterion function to make K value most suitable. The structure sometimes consumes more storage than R-Link but gains better performance. The more the data quantity, the better the overall performance of the structure.

Key words: spatial database, R-Link tree, quadtree, spatial clustering, spatial index

中图分类号: 

  • TP301.6