一种改进R-Link的空间数据检索算法

An Improved R-Link Spatial Data Index Algorithm

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.

This paper presents a quick speed spatial indexing introduced K-Means algorithm into the structure. In K-Means structure which is based on R-link tree. And we 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.