不确定数据上范围受限的最近邻查询算法

不确定数据的查询处理是数据库领域近年来的热点研究课题.提出一种不确定数据上的范围受限的最近邻查询.给定不确定数据集D={o1,o2,…,on},范围约束R是一个简单多边形,q为一固定的查询点,范围受限的最近邻查询返回的是在数据集D中,既满足范围约束R,又能成为查询点q的最近邻的对象集合.为处理该查询,提出了范围受限的最近邻核心集的概念和范围受限的最近邻核心集的查找算法.并提出一种计算范围受限的最近邻候选集的优化方法,降低了查询代价.最后通过实验验证了该算法的有效性.

Nearest Neighbor Queries with Range Constrained on Uncertain Data

Recently,query processing based on uncertain data are becoming research focuses.Nearest neighbor queries with range constrained(CNN) on uncertain data is proposed in this paper.Given a set of uncertain objects D={o1,o2,…,on},Range R constrained with simple polygons,a certain query object q,a CNN query returns from D,the set of objects that are among the nearest neighbors of q;meanwhile,contained in R.To address this query,CNN-core is defined in this paper,And an efficient algorithm to find CNN-core is provided in this paper.An effective method to computing the candidate is also proposed,reducing the query cost.Finally,the experimental results show that the algorithm is efficient and effective.