Clustering, Encoding and Diameter Computation Algorithms for Multidimensional Data
Data Structures and Algorithms
2010-09-14 v1 Computational Geometry
Abstract
In this paper we present novel algorithms for several multidimensional data processing problems. We consider problems related to the computation of restricted clusters and of the diameter of a set of points using a new distance function. We also consider two string (1D data) processing problems, regarding an optimal encoding method and the computation of the number of occurrences of a substring within a string generated by a grammar. The algorithms have been thoroughly analyzed from a theoretical point of view and some of them have also been evaluated experimentally.
Cite
@article{arxiv.1009.2160,
title = {Clustering, Encoding and Diameter Computation Algorithms for Multidimensional Data},
author = {Mugurel Ionut Andreica and Eliana-Dina Tirsa},
journal= {arXiv preprint arXiv:1009.2160},
year = {2010}
}
Comments
ISBN: 978-973-662-574-9