On data clustering: exact and approximate solutions

Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneous and/or well separated. In the last decades, cluster analysis started playing an important role in a wide and heterogenous range of applications involving different scientific research communities, including among others genetics, biology, biochemistry, mathematics, and computer science. This paper overviews the main types of clustering and criteria for homogeneity or separation and the most popular solution techniques.