Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments.

Data Clustering: Theory, Algorithms, and Applications, Second Edition:

covers the basics of data clustering,
includes a list of popular clustering algorithms, and
provides program code that helps users implement clustering algorithms.