A cost model for incremental nearest neighbor search in multidimensional spaces

被引：0
|
作者：
Feng, Yaokai [1 ]
Makinouchi, Akifumi [1 ]
Kaneko, Kunihiko [1 ]
机构：
[1] Kyushu Univ, Grad Sch Informat Sci & Elect Engn, Fukuoka 812, Japan
来源：
2007 INTERNATIONAL CONFERENCE ON INTELLIGENT PERVASIVE COMPUTING, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/IPC.2007.20
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Nearest Neighbor (NN) search has been widely used in spatial databases and multimedia databases. Incremental NN (INN) search is regarded as the optimal NN search because of the minimum number of node accesses and it can be used no matter whether the number of objects to be retrieved is fixed or not in advance. R*-tree is still regarded as being among the best high-dimensional indices. This paper presents an analytical model for estimating performance of the INN search algorithm on R*-tree. The theoretical analysis is verified by experiments.
引用
收藏
页码：111 / 116
页数：6
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