ENGLISH

Mining Sequential Patterns from Large Data Sets

By Wei Wang , Jiong Yang

Book information

Publisher
Springer
Year
2005
ISBN
9780387242460, 0-387-24246-5, 0387242473
LCC
QA76.9.D343 M557 2005
Open Library ID
OL3311977M
Language
english
Format
PDF
Filesize
8 MB (8053964 bytes)
Series
The Kluwer international series on advances in database systems 28
Edition
1
Pages
173\173
Library
mexmat
Time added
2009-07-20 03:45:11

Description

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.

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