Advanced Methods for Knowledge Discovery from Complex Data

Maulik, Ujjwal|Holder, Lawrence B.|Cook, Diane J.

ISBN 10: 1849969914 / ISBN 13: 9781849969918

Published by Springer London, 2010

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers a variety of advanced data mining techniquesDoes not limit discussion to one specific domain areaFirst book to focus on advances on the synergy between application domains and algorithm types rather than limit the scope to a particul.

Seller Inventory # 4289035

Bibliographic Details

• Title: Advanced Methods for Knowledge Discovery from Complex Data
• Publisher: Springer London
• Publication Date: 2010
• Language: English
• ISBN 10: 1849969914
• ISBN 13: 9781849969918
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Knowledge discovery takes the raw results from data mining (the process of extracting trends or patterns from data) and carefully and accurately transforms them into useful and understandable information. In this book, active practitioners and leading researchers detail recent advances in knowledge discovery. Coverage presents a good balance of introductory material on the knowledge discovery process, advanced issues, and state-of-the-art tools and techniques. An overview of the field, looking at the issues and challenges involved, is followed by coverage of recent trends and important applications of advanced data mining techniques in areas such as life sciences, world-wide web, image databases, cyber security, and sensor networks.

From the Back Cover

Advanced Methods for Knowledge Discovery from Complex Data brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery, where the information is mined from complex data, such as unstructured text from the world-wide web, databases naturally represented as graphs and trees, geoscientific data from satellites and visual images, multimedia data and bioinformatics data.

An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining, including descriptions of some currently popular tools like genetic algorithms, neural networks and case-based reasoning. This provides the context for the subsequent chapters on methods and applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links and sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional and complex domains, such as life sciences, world-wide web, image databases, cyber security and sensor networks.

With a good balance of introductory material on the knowledge discovery process, advanced issues and state-of-the-art tools and techniques, as well as recent working applications this book provides a representative selection of the available methods and their evaluation in real domains. It will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field. A website supports the book: http://www.cse.uta.edu/amkdcd.