BUAP: Performance of K-Star at the INEX΄09 Clustering Task.

The aim of this paper is to use unsupervised classification techniques in order to group the documents of a given huge collection into clusters. We approached this challenge by using a simple clustering algorithm (K-Star) in a recursive clustering process over subsets of the complete collection. The presented approach is a scalable algorithm which may automatically discover the number of clusters. The obtained results outperformed different baselines presented in the INEX 2009 clustering task. [ABSTRACT FROM AUTHOR]