Segmentation problems

被引:56
作者
Kleinberg, J
Papadimitriou, C
Raghavan, P
机构
[1] Cornell Univ, Dept Comp Sci, Ithaca, NY 14853 USA
[2] Univ Calif Berkeley, Berkeley, CA 94720 USA
[3] Verity, Sunnyvale, CA 94089 USA
关键词
clustering; data mining; approximation algorithms; market segmentation;
D O I
10.1145/972639.972644
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We study a novel genre of optimization problems, which we call segmentation problems, motivated in part by certain aspects of clustering and data mining. For any classical optimization problem, the corresponding segmentation problem seeks to partition a set of cost vectors into several segments, so that the overall cost is optimized. We focus on two natural and interesting (but MAXSNP-complete) problems in this class, the HYPERCUBE SEGMENTATION PROBLEM and the CATALOG SEGMENTATION PROBLEM, and present approximation algorithms for them. We also present a general greedy scheme, which can be specialized to approximate any segmentation problem.
引用
收藏
页码:263 / 280
页数:18
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