@article {IIIA-2002-447,
title = {Hierarchical Spherical Clustering},
journal = {Int. J. of Uncertainty Fuzziness and Knowledge-Based Systems},
volume = {10},
number = {2},
year = {2002},
pages = {157-172},
abstract = {This work introduces an alternative representation for large dimensional data sets. Instead of using 2D or 3D representations, data is located on the surface of a sphere. Together with this representation, a hierarchical clustering algorithm is defined to analyse and extract the structure of the data. The algorithm builds a hierarchical structure (a dendrogram) in such a way that different cuts of the structure lead to different partitions of the surface of the sphere. This can be seen as a set of concentric spheres, each one being of different granularity. Also, to obtain an initial assignment of the data on the surface of the sphere, a method based on Sammon{\textquoteright}s mapping has been developed.},
author = {Vicen{\c c} Torra and Sadaaki Miyamoto}
}