Advances in Knowledge Discovery and Data Mining (Paperback)

by Usama M. Fayyad (Author), Gregory Piatetsky-Shapiro (Author), Padhraic Smyth (Author), Ramasamy Uthurusamy (Author)

Editorial Reviews

Product Description
Advances in Knowledge Discovery and Data Mining brings together the latest research -- in statistics, databases, machine learning, and artificial intelligence -- that are part of the exciting and rapidly growing field of Knowledge Discovery and Data Mining. Topics covered include fundamental issues, classification and clustering, trend and deviation analysis, dependency modeling, integrated discovery systems, next generation database systems, and application case studies. The contributors include leading researchers and practitioners from academia, government laboratories, and private industry. The last decade has seen an explosive growth in the generation and collection of data. Advances in data collection, widespread use of bar codes for most commercial products, and the computerization of many business and government transactions have flooded us with data and generated an urgent need for new techniques and tools that can intelligently and automatically assist in transforming this data into useful knowledge. This book is a timely and comprehensive overview of the new generation of techniques and tools for knowledge discovery in data. Distributed for AAAI Press

Additional information on Advances in Knowledge Discovery and Data Mining

About the Author
Usama M. Fayyad heads the Machine Learning Systems Group at the Jet Propulsion Laboratory, California Institute of Technology and is an Adjunct Assistant Professor of Computer Science at the University of Southern California. Gregory Piatetsky-Shapiro is a Principal Member of Technical Staff and a Principal Investigator of KDD project at GTE Laboratories. Padhraic Smyth is a Technical Group Leader at the Jet Propulsion Laboratory. Ramasamy Uthurusamy is Machine Learning Project Leader at the General Motors R&D Center.

Product Details

• Paperback: 560 pages
• Publisher: The MIT Press (February 1, 1996)
• Language: English
• ISBN-10: 0262560976
• ISBN-13: 978-0262560979
• Product Dimensions: 8.9 x 6 x 1.3 inches
• Shipping Weight: 1.9 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars See all reviews (2 customer reviews)
• Amazon.com Sales Rank: #1,004,963 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

0 of 1 people found the following review helpful:

5.0 out of 5 stars Primer++, February 27, 2009

By	Sameer Yami (Silicon Valley, CA, USA) - See all my reviews (REAL NAME)

This book has a bunch of papers in various fields associated with datamining and thus provides a very good primer to people who want to understanding datamining and then go into the details as the need arises.

28 of 62 people found the following review helpful:

5.0 out of 5 stars An excellent book., December 11, 1997

By A Customer

I read a lot of papers from this book. And I read twice and twice a lot of them. This is a book to the professional and to the novice in data mining (d.m.). In it you take a general view from data mining and the particular one you pretend because you can see papers from "what is d.m.", "how to use d.m.", "d.m. techniques", "d.m. and visualization", "applications from d.m.", "d.m. tools", "advances in d.m.", "the future and d.m.".