Data Mining: Theory, Methodology, Techniques, and Applications (Lecture Notes in Computer Science, 3755)

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. The original papers were initially reviewed for the workshops, conferences and forums. The 25 articles in this state-of-the-art survey were carefully reviewed and selected from numerous contributions during at least two rounds of reviewing and improvement for inclusion in the book. They provide an interesting and broad update on current research and development in data mining. The book is divided into two parts. It starts with state-of-the-art research papers organized in topical sections on methodological advances, data linkage, text mining, and temporal and sequence mining. The second part comprises papers on state-of-the-art industrial applications from the fields of health, finance and retail Front Matter....Pages - Generality Is Predictive of Prediction Accuracy....Pages 1-13 Visualisation and Exploration of Scientific Data Using Graphs....Pages 14-27 A Case-Based Data Mining Platform....Pages 28-38 Consolidated Trees: An Analysis of Structural Convergence....Pages 39-52 K Nearest Neighbor Edition to Guide Classification Tree Learning: Motivation and Experimental Results....Pages 53-63 Efficiently Identifying Exploratory Rules’ Significance....Pages 64-77 Mining Value-Based Item Packages – An Integer Programming Approach....Pages 78-89 Decision Theoretic Fusion Framework for Actionability Using Data Mining on an Embedded System....Pages 90-104 Use of Data Mining in System Development Life Cycle....Pages 105-117 Mining MOUCLAS Patterns and Jumping MOUCLAS Patterns to Construct Classifiers....Pages 118-129 A Probabilistic Geocoding System Utilising a Parcel Based Address File....Pages 130-145 Decision Models for Record Linkage....Pages 146-160 Intelligent Document Filter for the Internet....Pages 161-175 Informing the Curious Negotiator: Automatic News Extraction from the Internet....Pages 176-191 Text Mining for Insurance Claim Cost Prediction....Pages 192-202 An Application of Time-Changing Feature Selection....Pages 203-217 A Data Mining Approach to Analyze the Effect of Cognitive Style and Subjective Emotion on the Accuracy of Time-Series Forecasting....Pages 218-228 A Multi-level Framework for the Analysis of Sequential Data....Pages 229-243 Hierarchical Hidden Markov Models: An Application to Health Insurance Data....Pages 244-259 Identifying Risk Groups Associated with Colorectal Cancer....Pages 260-272 Mining Quantitative Association Rules in Protein Sequences....Pages 273-281 Mining X-Ray Images of SARS Patients....Pages 282-294 The Scamseek Project – Text Mining for Financial Scams on the Internet....Pages 295-302 A Data Mining Approach for Branch and ATM Site Evaluation....Pages 303-318 The Effectiveness of Positive Data Sharing in Controlling the Growth of Indebtedness in Hong Kong Credit Card Industry....Pages 319-329 Back Matter....Pages -

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.