Exact and approximation algorithms for clustering

被引：132
|
作者：
Agarwal, PK [1 ]
Procopiuc, CM [1 ]
机构：
[1] Duke Univ, Dept Comp Sci, Ctr Geometr Comp, Durham, NC 27708 USA
来源：
ALGORITHMICA | 2002年 / 33卷 / 02期
关键词：
k-center clustering; capacitated clustering; approximation algorithms;
D O I：
10.1007/s00453-001-0110-y
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In this paper we present an n(O(k1-1/d))-time algorithm for solving the k-center problem in R-d, under L-infinity- and L-2-metrics. The algorithm extends to other metrics, and to the discrete k-center problem. We also describe a simple (1 + epsilon)-approximation algorithm for the k-center problem, with running time O(n log k) + (k/epsilon)(O(k1-1/d)). Finally, we present an n(O(k1-1/d))-time algorithm for solving the L-capacitated k-center problem, provided that L = Omega(n/k(1-1/d)) or L = O(I).
引用
收藏
页码：201 / 226
页数：26
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