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Advanced Methods for Knowledge Discovery from Complex Data (Advanced Information and Knowledge Processing)

Advanced Methods for Knowledge Discovery from Complex Data (Advanced Information and Knowledge Processing) Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

This book brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery. An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining. 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, this book will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field.

Table of Contents

Foundations: Knowledge Discovery and Data Mining.- Automatic Discovery of Class Hierarchies via Output Space.- Graph-based Mining of complex Data.- Predictive Graph Mining with Kernel Methods.- TREEMINER: An Efficient Algorithm for Mining Embedded Ordered Frequent Trees.- Sequence Data Mining.- Link-based Classification.- Applications: Knowledge Discovery from Evolutionary Trees.- Ontology-assisted Mining of RDF Documents.- Image Retrieval using Visual Features and Relevance Feedback.- Significant Feature Selection Using Computational Intelligent Techniques for Intrusion Detection.- On-board Mining of Data Streams in Sensor Networks.- Discovering Evolutionary Classifier over High Speed Non-static Stream.

Product Details

ISBN:
9781849969918
Publisher:
Springer
Location:
London
Author:
Maulik, Ujjwal
Author:
Cook, Diane J.
Author:
Holder, Lawrence B.
Subject:
Artificial Intelligence
Subject:
Bayesian Networks
Subject:
Data mining
Subject:
Spatial/Temporal Data Mining)
Subject:
Graphical Data
Subject:
Knowledge Discovery
Subject:
Machine learning
Subject:
Soft Computing and Structure Discovery
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Database management
Subject:
Information storage and retrieval.
Subject:
Pattern recognition.
Subject:
Algorithm Analysis and Problem Complexity
Subject:
Image Processing and Computer Vision
Subject:
Computers-Reference - General
Subject:
Data Mining (& Spatial/Temporal Data Mining)
Subject:
Computer Science
Subject:
Language, literature and biography
Subject:
Information storage and retrieva
Subject:
Optical pattern recognition
Subject:
Computer software
Subject:
Computer Vision
Copyright:
Edition Description:
Softcover reprint of hardcover 1st ed. 2005
Series:
Advanced Information and Knowledge Processing
Publication Date:
20101213
Binding:
TRADE PAPER
Language:
English
Pages:
388
Dimensions:
235 x 155 mm 582 gr

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Database » Design
Computers and Internet » Personal Computers » General
Computers and Internet » Software Engineering » Software Management

Advanced Methods for Knowledge Discovery from Complex Data (Advanced Information and Knowledge Processing)
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Product details 388 pages Not Avail - English 9781849969918 Reviews:
"Synopsis" by , This book brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery. An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining. 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, this book will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field.
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