摘要
大数据时代已经来临,海量数据计算要求设计亚线性算法。本文选择了大数据分析问题中比较重要的问题、即近邻问题,包括近似最近邻问题、近似k-最近邻问题以及全k-最近邻问题,对其亚线性算法的研究现状做了综述。
The era of big data has come,and massive data computing requires the design of sub-linear algorithms.This paper chooses several important problems in big data analysis,namely the Nearest Neighbors problems,including the All-k-Nearest Neighbors,Approximate Nearest Neighbors and Approximate k-Nearest Neighbors problem,and provides a survey on the sub-linear algorithms about these problems.
作者
马恒钊
李建中
MA Hengzhao;LI Jianzhong(Research Institute of Massive Data Computing,Harbin Institute of Technology,Harbin 150001,China;Shenzhen University of Science and Technology,Chinese Academy of Sciences,Shenzhen Guangdong 518107,China)
出处
《智能计算机与应用》
2022年第6期1-6,共6页
Intelligent Computer and Applications
基金
国家自然科学基金(61832003)
关键词
全k-最近邻
近似最近邻
近似k-最近邻
亚线性算法
All-k-Nearest Neighbors
Approximate Nearest Neighbors
Approximate k-Nearest Neighbors
sub-linear algorithms
