Sciweavers

Share
CPM
2000
Springer

Approximation Algorithms for Hamming Clustering Problems

11 years 5 months ago
Approximation Algorithms for Hamming Clustering Problems
We study Hamming versions of two classical clustering problems. The Hamming radius p-clustering problem (HRC) for a set S of k binary strings, each of length n, is to find p binary strings of length n that minimize the maximum Hamming distance between a string in S and the closest of the p strings; this minimum value is termed the p-radius of S and is denoted by . The related Hamming diameter p-clustering problem (HDC) is to split S into p groups so that the maximum of the Hamming group diameters is minimized; this latter value is called the p-diameter of S. We provide an integer programming formulation of HRC which yields exact solutions in polynomial time whenever k is constant. We also observe that HDC admits straightforward polynomial-time solutions when k = O(logn) and p = O(1), or when p = 2. Next, by reduction from the corresponding geometric p-clustering problems in the plane under the L1 metric, we show that neither HRC nor HDC can be approximated within any constant factor ...
Leszek Gasieniec, Jesper Jansson, Andrzej Lingas
Added 02 Aug 2010
Updated 02 Aug 2010
Type Conference
Year 2000
Where CPM
Authors Leszek Gasieniec, Jesper Jansson, Andrzej Lingas
Comments (0)
books