Table of Contents

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   Book Overview
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   Chapter 1 Perspective on Data Mining from Statistical Viewpoints
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   Chapter 2 Inductive Databases and Knowledge Scouts
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   Chapter 3 Hyperlink-Aware Mining and Analysis of the Web
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   Chapter 4 Polynomial Time Matching Algorithms for Tree-Like Structured Patterns in Knowledge Discovery
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   Chapter 5 Fast Discovery of Interesting Rules
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   Chapter 6 Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases
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   Chapter 7 Minimum Message Length Criterion for Second-Order Polynomial Model Discovery
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   Chapter 8 Frequent Itemset Counting Across Multiple Tables
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    Chapter 9 Frequent Closures as a Concise Representation for Binary Data Mining
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    Chapter 10 An Optimization Problem in Data Cube System Design
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    Chapter 11 Exception Rule Mining with a Relative Interestingness Measure
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    Chapter 12 Consistency Based Feature Selection
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    Chapter 13 Feature Selection for Clustering
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    Chapter 14 A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases
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    Chapter 15 Missing Value Estimation Based on Dynamic Attribute Selection
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    Chapter 16 On Association, Similarity and Dependency of Attributes
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    Chapter 17 Prototype Generation Based on Instance Filtering and Averaging
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    Chapter 18 A Visual Method of Cluster Validation with Fastmap
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    Chapter 19 COE: Clustering with Obstacles Entities A Preliminary Study
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    Chapter 20 Combining Sampling Technique with DBSCAN Algorithm for Clustering Large Spatial Databases
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    Chapter 21 Predictive Adaptive Resonance Theory and Knowledge Discovery in Databases
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    Chapter 22 Improving Generalization Ability of Self-Generating Neural Networks Through Ensemble Averaging
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    Chapter 23 Attribute Transformations on Numerical Databases
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    Chapter 24 Efficient Detection of Local Interactions in the Cascade Model
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    Chapter 25 Extracting Predictors of Corporate Bankruptcy: Empirical Study on Data Mining Methods
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    Chapter 26 Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets
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    Chapter 27 Discovering Protein Functional Models Using Inductive Logic Programming
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    Chapter 28 Mining Web Transaction Patterns in an Electronic Commerce Environment
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    Chapter 29 Making Use of the Most Expressive Jumping Emerging Patterns for Classification
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    Chapter 30 Mining Structured Association Patterns from Databases
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    Chapter 31 Association Rules
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    Chapter 32 Density-Based Mining of Quantitative Association Rules
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    Chapter 33 AViz: A Visualization System for Discovering Numeric Association Rules
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    Chapter 34 Discovering Unordered and Ordered Phrase Association Patterns for Text Mining
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    Chapter 35 Using Random Walks for Mining Web Document Associations
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    Chapter 36 A Concurrent Approach to the Key-Preserving Attribute-Oriented Induction Method
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    Chapter 37 Scaling Up a Boosting-Based Learner via Adaptive Sampling
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    Chapter 38 Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
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    Chapter 39 Robust Ensemble Learning for Data Mining
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    Chapter 40 Interactive Visualization in Mining Large Decision Trees
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    Chapter 41 VQTree: Vector Quantization for Decision Tree Induction
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    Chapter 42 Making Knowledge Extraction and Reasoning Closer
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    Chapter 43 Discovery of Relevant Weights by Minimizing Cross-Validation Error
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    Chapter 44 Efficient and Comprehensible Local Regression
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    Chapter 45 Information Granules for Spatial Reasoning
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    Chapter 46 Uncovering the Hierarchical Structure of Text Archives by Using an Unsupervised Neural Network with Adaptive Architecture
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    Chapter 47 Mining Access Patterns Efficiently from Web Logs
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    Chapter 48 A Comparative Study of Classification Based Personal E-mail Filtering
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    Chapter 49 Extension of Graph-Based Induction for General Graph Structured Data
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    Chapter 50 Text-Source Discovery and GlOSS Update in a Dynamic Web
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    Chapter 51 Extraction of Fuzzy Clusters from Weighted Graphs
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    Chapter 52 Text Summarization by Sentence Segment Extraction Using Machine Learning Algorithms