计算机科学与探索2010，Vol.4Issue(10)：881-889,9.DOI:10.3778/j.issn.1673-9418.2010.10.002
多维度量空间中发现相互kNN
Finding Mutual k-Nearest Neighbors in Multi-Metric Space
摘要
Abstract
Finding mutual k-nearest neighbors in two kinds of objects can provide decisions for applications such as job matching and college selection.Existing methods mainly focus on processing mutual nearest neighbor queries in one single metric space(e.g.L2 norm)and this will probably lead to an unfair assignment.This paper formally explores the problem of mutual nearest neighbors in multi-metric space.Based on space indices,algorithms are proposed for finding mutual k-nearest neighbors in multi-metric space.With the synthetic dataset, the algorithms are experimentally evaluated for a wide range of variable settings, and show that the proposed solutions outperform alternative brute force methods.关键词
相互k最近邻/多度量空间/R树/Minkowski区域Key words
mutual k-nearest neighbors/multi-metric space/R-tree/Minkowski region分类
信息技术与安全科学引用本文复制引用
刘俊岭,孙焕良..多维度量空间中发现相互kNN[J].计算机科学与探索,2010,4(10):881-889,9.基金项目
The National Natural Science Foundation of China under Grant No.61070024(国家自然科学基金) （国家自然科学基金）
The Natural Science Founda tion of Liaoning Province of China under Grant No.20071004(辽宁省自然科学基金):the Foundation of Education Department of iaoning Province of China under Grant No.2008600,2008596(辽宁省教育厅基金). （辽宁省自然科学基金）
