We have developed a novel algorithm for cluster analysis that is based on g
raph theoretic techniques. A similarity graph is defined and clusters in th
at graph correspond to highly connected subgraphs. A polynomial algorithm t
o compute them efficiently is presented. Our algorithm produces a solution
with some provably good properties and performs well on simulated and real
data. (C) 2000 Elsevier Science B.V. All rights reserved.