Sequence Data Mining (Hardcover, 2007 ed.)

Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place. Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering. Forward by Professor Jiawei Han, University of Illinois at Urbana-Champaign.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Advances in Database Systems, 33
Release date:	August 2007
First published:	August 2007
Authors:	Guozhu Dong • Jian Pei
Dimensions:	235 x 156 x 16mm (L x W x T)
Format:	Hardcover
Pages:	150
Edition:	2007 ed.
ISBN-13:	978-0-387-69936-3
Categories:	Books > Computing & IT > Applications of computing > Databases > Data capture & analysis Promotions
LSN:	0-387-69936-8
Barcode:	9780387699363

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