Data Mining: Multimedia, Soft Computing, and Bioinformatics / Edition 1

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  • 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
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Editorial Reviews

From the Publisher

"…an excellent primer on the subject of data mining with an accessible introduction to the fundamental and advanced data mining technologies." (Journal of Electronic Imaging, January-March 2006)

"Applied statisticians and probabilists will like this book very much." (Journal of Statistical Computation and Simulation, November 2005)

"…the book is an impressive and broad overview...a general roadmap of what methods are available and where to look." (Journal of Intelligent & Fuzzy Systems, Vol. 16, No. 2, 2005)

"This readable survey describes multimedia, soft computing, and bioinformatics strategies for a number of data types…" (Business Horizons, September- October 2004)

"…an accessible introduction to fundamental and advanced data mining technologies. It will be an excellent book for both beginners and professionals." (Computing, April 20, 2004)

"Overall, this is a nice, easy-to-read book for those already working in the area of data mining." (Technometrics, August 2004, Vol. 46, No. 3)

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Product Details

  • ISBN-13: 9780471460541
  • Publisher: Wiley
  • Publication date: 9/12/2003
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 424
  • Product dimensions: 6.32 (w) x 9.37 (h) x 0.99 (d)

Meet the Author

SUSHMITA MITRA, PHD, is a Professor at Machine Intelligence Unit, Indian Statistical Institute, in Calcutta. She is a coauthor of Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing, also published by Wiley.

TINKU ACHARYA, PHD, Senior Executive vice president and Chief Science Officer of Avisere Inc., Tucson, Arizona, is involved in multimedia data mining applications. He is also an adjunct professor in the Department of Electrical Engineering at Arizona State University. He was recognized as the Most Prolific Inventor of Intel Corporation Worldwide in 1999.

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Table of Contents


1. Introduction to Data Mining.

2. Soft Computing.

3. Multimedia Data Compression.

4. String Matching.

5. Classification in Data Mining.

6. Clustering in Data Mining.

7. Association Rules.

8. Rule Mining with Soft Computing.

9. Multimedia Data Mining.

10. Bioinformatics: An Application.


About the Authors.

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