Book: Data Clustering: Algorithms and Applications
The chapters are carefully constructed to cover the area of clustering comprehensively with up-to-date surveys, making this book accessible to beginning data scientists and analysts.
Book Announcement: Data Clustering: Algorithms and Applications
Editors: Charu C. Aggarwal and Chandan K. Reddy
CRC Press, September 2013
Approximately 620 pages
This is an edited book on data clustering.
The set of chapters, the
individual authors and the material in
each chapters are carefully constructed
so as to cover the area of clustering
comprehensively with up-to-date surveys.
Each chapter contains carefully organized
material, which includes introductory material
as well as advanced material from the recent literature.
Thus, the book can also be used as a reference aid.
Emphasis was placed on simplifying the content,
so that the material is relatively easy to assimilate.
The book assumes relatively little prior
background, other than a basic understanding
of probability and statistical concepts.
Therefore, in spite of its deep coverage, it can
also provide a good introduction to the beginner.
Chapters cover one of three areas:
(i) Methods and techniques commonly used in data clustering,
such as feature selection issues, probabilistic methods,
distance-based methods, density-based methods, grid-based methods,
non-negative matrix factorization, and spectral methods.
In addition, special chapters are devoted to scalability and
big data issues, streaming data, and high dimensional data.
(ii) data domains, such as, text, categorical, mixed-attribute,
time-series, discrete sequence, uncertain and network data;
(iii) key enhancements of cluster analysis with semi-supervision,
human feedback, multi-view methods, and ways of measuring
effectiveness with validation techniques.
The table of contents and introductory chapter may be found at: