Clustering
Clustering a set of points into a few groups is frequently used for
statistical analysis and classification in numerous applications,
including information retrieval, facility location, data mining,
spatial data bases, data compression, image processing, astrophysics,
and scientific computing.
The abstract problem is as follows: given a set S of n points in a
d-dimensional metric space (R^d, rho) and an integer k, cover
S by k congruent disks (under the rho-metric) of smallest
possible radius.
Selected bibliography
- P. K. Agarwal
and C. M. Procopiuc.
Covering points by strips in the plane, 1998.
Unpublished manuscript.
- P. K. Agarwal
and C. M. Procopiuc.
Exact and approximation algorithms for clustering.
In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 658-667,
1998.
(PostScript)
- P. K. Agarwal,
M. Sharir, and E. Welzl.
The discrete 2-center problem.
In Proc. ACM Symp. on Computational Geometry, pages 147-155,
1997.
(PostScript)
- M. Wang, B. Iyer, and
J. S. Vitter.
Scalable mining for classification rules in relational databases.
In Proc. International Database Engineering & Application
Symposium, pages 58-67, 1998.