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Advances in Database Systems

Mining Sequential Patterns from Large Data Sets

Authors: Wang, Wei, Yang, Jiong

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Hardcover $169.00
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About this book

The focus of Mining Sequential Patterns from Large Data Sets is on sequential pattern mining.  In many applications, such as bioinformatics, web access traces, system utilization logs, etc., the data is naturally in the form of sequences.  This information has been of great interest for analyzing the sequential data to find its inherent characteristics.  Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces.

To meet the different needs of various applications, several models of sequential patterns have been proposed.   This volume not only studies the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. 

Mining Sequential Patterns from Large Data Sets provides a set of tools for analyzing and understanding the nature of various sequences by identifying the specific model(s) of sequential patterns that are most suitable.  This book provides an efficient algorithm for mining these patterns.

Mining Sequential Patterns from Large Data Sets is designed for a professional audience of researchers and practitioners in industry and also suitable for graduate-level students in computer science. 

Table of contents (1 chapters)

Buy this book

eBook $129.00
price for USA
  • ISBN 978-0-387-24247-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $169.00
price for USA
  • ISBN 978-0-387-24246-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $169.00
price for USA
  • ISBN 978-1-4419-3707-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Mining Sequential Patterns from Large Data Sets
Authors
Series Title
Advances in Database Systems
Series Volume
28
Copyright
2005
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-0-387-24247-7
DOI
10.1007/b104937
Hardcover ISBN
978-0-387-24246-0
Softcover ISBN
978-1-4419-3707-0
Series ISSN
1386-2944
Edition Number
1
Number of Pages
XV, 163
Topics