基于空间聚类的空间索引结构优化算法

Wang Jing-bin, Peng Zhi-xing
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引用次数: 5

摘要

空间索引是近年来数据库研究的热点之一。Guttman提出的r树可能是最流行的动态索引结构,它可以根据对象的空间位置从空间数据库中高效地检索对象。本文通过深入研究r树的各种操作,结合改进的k-介质聚类算法,提出了一种构造r树的新方法。基于该方法的r树结构更加紧凑,与传统的r树相比具有更多的优势。研究结果表明,由于结构的优化,所提出的方法可以有效地提高指标效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Optimization Algorithm for Spatial Index Structure Based on Spatial Clustering
Spatial index has been one of the active focus areas in recent database research. The R-tree proposed by Guttman is probably the most popular dynamic index structure for efficiently retrieving objects from a spatial database according to their spatial locations. This paper proposes a new method of constructing R-tree by studying every kind of its operations thoroughly and combining with improved k-medoids clustering algorithm. Because of its more compact structure, the R-tree based on this method has more advantages compared with traditional Rtree. The results of the study show that, due to the optimization of structure, the proposed method can improve index efficiency effectively.
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