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Data Mining

Theory, Methodology, Techniques, and Applications

By: Graham J. Williams (Editor), Simeon J. Simoff (Editor)

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Paperback | 20 February 2006

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352 Pages

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22.86 x 15.24 x 1.91

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This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums. Authors include some of Australia's leading researchers and practitioners in data mining. The volume also contains chapters by regional and international authors.

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Non-Fiction Computing & I.T.Databases Data Mining Data Capture & Analysis Computer Science Artificial Intelligence Computer Vision Pattern Recognition

Generality is predictive of prediction accuracy	p. 1
Visualisation and exploration of scientific data using graphs	p. 14
A case-based data mining platform	p. 28
Consolidated trees : an analysis of structural convergence	p. 39
K nearest neighbor edition to guide classification tree learning : motivation and experimental results	p. 53
Efficiently identifying exploratory rules' significance	p. 64
Mining value-based item packages - an integer programming approach	p. 78
Decision theoretic fusion framework for actionability using data mining on an embedded system	p. 90
Use of data mining in system development life cycle	p. 105
Mining MOUCLAS patterns and jumping MOUCLAS patterns to construct classifiers	p. 118
A probabilistic geocoding system utilising a parcel based address file	p. 130
Decision models for record linkage	p. 146
Intelligent document filter for the Internet	p. 161
Informing the curious negotiator : automatic news extraction from the Internet	p. 176
Text mining for insurance claim cost prediction	p. 192
An application of time-changing feature selection	p. 203
A data mining approach to analyze the effect of cognitive style and subjective emotion on the accuracy of time-series forecasting	p. 218
A multi-level framework for the analysis of sequential data	p. 229
Hierarchical hidden Markov models : an application to health insurance data	p. 244
Identifying risk groups associated with colorectal cancer	p. 260
Mining quantitative association rules in protein sequences	p. 273
Mining x-ray images of SARS patients	p. 282
The Scamseek project - text mining for financial scams on the Internet	p. 295
A data mining approach for branch and ATM site evaluation	p. 303
The effectiveness of positive data sharing in controlling the growth of indebtedness in Hong Kong credit card industry	p. 319
Table of Contents provided by Blackwell. All Rights Reserved.

Data Mining

Theory, Methodology, Techniques, and Applications

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

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