摘要
针对动态R-树是通过动态插入算法建立起来的,其节点分裂算法的性能直接影响到R-树的性能和查询效率的问题,为了使动态R-树适应多维复杂空间数据的要求,提出一种用于实现R-树节点分裂的混合聚类算法(HCR),它建立在普通聚类算法的基础上,并进行了一系列扩充。针对空间对象的均匀分布与不均匀分布,HCR算法在实现R-树节点分裂时分别采用不同的聚类准则以提高其聚类效果和查询效率。此外,还将HCR算法与其他算法进行对比实验,结果表明该算法具有较高的查询效率。
Considering that dynamic R-tree is implemented by dynamic insertion algorithm, and its quality of splitting algorithm influences directly the performance of R-tree and querying efficiency, in order to meet the demands of multi-dimension and complex spatial data, the hybrid clustering （HCR） algorithm was proposed for the nodes splitting of R-tree which was based on the common clustering algorithms, and some extensions were built. According to the difference of spatial objects distributed evenly and unevenly, different clustering rules were adopted to improve the query efficiency. Some comparisons and experiments were conducted. The results show that the hybrid clustering algorithm has high efficiency in querying.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第2期366-370,共5页
Journal of Central South University:Science and Technology
基金
湖南省自然科学基金资助项目(04JJ30046)
