Mining Sequential Patterns from Large Data Sets

Wei Wang, Jiong Yang - Collection International Series on Advances in Database Systems

170 pages, parution le 10/06/2005

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Résumé

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.

Written for: Professional audience of researchers and practitioners in industry, graduate-level students in computer science

Sommaire

List of Figures
List of Tables
Preface
Introduction
Related Work
Period
Statistically Significant Patterns
Approximate Patterns
Conclusion Remark
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Wei Wang, Jiong Yang
Collection	International Series on Advances in Database Systems
Parution	10/06/2005
Nb. de pages	170
Format	16 x 24
Couverture	Relié
Poids	445g
Intérieur	Noir et Blanc
EAN13	9780387242460
ISBN13	978-0-387-24246-0