Covers the capabilities and limitations of constrained clustering. This title presents various types of constraints for clustering, describes useful variations of the standard problem of clustering under constraints, and applies clustering with constraints to relational, bibliographic, and video data.
From the Foreword "? this book shows how constrained clustering can be used to tackle large problems involving textual, relational, and even video data. After reading this book, you will have the tools to be a better analyst [and] to gain more insight from your data, whether it be textual, audio, video, relational, genomic, or anything else." -Dr. Peter Norvig, Director of Research, Google, Inc., Mountain View, California, USA
