【摘要】 目前空间数据相似性查询有着广泛的应用需求,解决相似性查询问题的一项关键技术就是高维空间数据索引。从分析高维空间数据的分布特性入手,探讨相似性查询中的高维空间数据检索问题,在此基础上,提出一种针对相似性查询的高维空间数据索引的分类方法,将高维空间数据索引分为三类:向量空间树型索引、基于向量近似的索引以及基于距离的索引,这种分类初步理顺了高维空间数据索引与相似性查询的关系,并以各类方法的代表性索引结构为例,分析指出各类高维索引方法的实现机理及其适应性,为相似性查询中索引技术的研究奠定了基础。更多还原

【Abstract】 Nowadays the applications of spatial data similarity search are widely needed,and high dimensional spatial data index becomes a key technology of similarity search.Beginning with analyzing the distribution of high dimensional spatial data,this paper discusses high dimensional spatial data retrieval in similarity search.Based on all the research,we propose a method to classify the high dimensional spatial data index technology for similarity search,which initially makes a clear distinction of the relationship between high dimensional spatial data index and similarity search.Then high dimensional spatial data index principle and the state of its applications in similarity search are analyzed with an example of typical index structure respectively,which lays a foundation for the research on index technology in spatial data similarity search.更多还原