Mining Sequential Patterns from Large Data Sets

Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining.

Mining Sequential Patterns from Large Data Sets

Author: Wei Wang

Publisher: Springer Science & Business Media

ISBN: 0387242473

Page: 163

View: 203

In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.

Related Books:

Mining Sequential Patterns from Large Data Sets
Language: un
Pages: 163
Authors: Wei Wang, Jiong Yang
Categories: Computers
Type: BOOK - Published: 2006-03-30 - Publisher: Springer Science & Business Media

In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models
Data Mining for Association Rules and Sequential Patterns
Language: un
Pages: 254
Authors: Jean-Marc Adamo
Categories: Computers
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

Recent advances in data collection, storage technologies, and computing power have made it possible for companies, government agencies and scientific laboratories to keep and manipulate vast amounts of data relating to their activities. This state-of-the-art monograph discusses essential algorithms for sophisticated data mining methods used with large-scale databases, focusing on
Principles of Data Mining and Knowledge Discovery
Language: en
Pages:
Authors: Jean-Marc Adamo
Categories: Data mining
Type: BOOK - Published: 2000 - Publisher:

Books about Principles of Data Mining and Knowledge Discovery
Data Mining Applications for Empowering Knowledge Societies
Language: en
Pages: 332
Authors: Hakikur Rahman
Categories: Business & Economics
Type: BOOK - Published: 2009 - Publisher: IGI Global

"This book presents an overview on the main issues of data mining, including its classification, regression, clustering, and ethical issues"--Provided by publisher.
KDD ...
Language: en
Pages:
Authors: Hakikur Rahman
Categories: Data mining
Type: BOOK - Published: 2006 - Publisher:

Books about KDD ...