Clustering can be used as independent data mining task for understanding the intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have compiled the latest advances in clustering large and high-dimensional data. Contributions, written by leading researchers from both academia and industry, including the basics of theoretical as well as application and evaluation of algorithms, and thus provides an excellent overview of state-of-the-art. Level of detail, breadth of coverage, and comprehensive bibliography make this book very suitable for researchers and graduate students in the field of data mining and in many other important areas of application concerned.