Data Mining : Multimedia, Soft Computing, and Bioinformatics

This book is a distinct addition to the field of data mining in its coverage of topics and ideas.The good point about this book is that it explains the central concepts in great details with the required rigour and also puts in examples to make them understandable. Its not a typical Theorem , Lemma book , but also do not shy away from the mathematical complexities.There is adequate coverage of all the standard topics and additionally there are interesting sections on Rough sets and Fuzzy sets, which are generally not available everywhere.The most important point about this book is that it gives a thorough coverage of Multimedia data and web data and biological data, which is very dificult to get in one place in any book.A researcher or anyone with adequate background in Mathematics will find this book very helpful in their research.References are also pretty much exhaustive.I would have liked to see some more coverage on datawarehouse and complexity analysis of the algorithms mentioned, also some language level implementation examples at least in some appendix to the book. Also a paperback edition is needed as the price is quite high.

• First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches
• Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining
• Discusses principles and classical algorithms on string matching and their role in data mining

• First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches
• Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining
• Discusses principles and classical algorithms on string matching and their role in data mining

"This survey describes data mining strategies for a slew of data types, including numeric and alpha-numeric formats, text, images, video, graphics, and the mixed representations therein. Along with traditional concepts and functions of data mining - like classification, clustering, and rule mining - the authors highlight topical issues in multimedia applications and bioinformatics."--Jacket The digital revolution has made digitized information easy to capture, process, store, distribute, and transmit [1]-[3].