The Handbook of Data Mining

Edited by Nong Ye, Lawrence Erlbaum Associates, Inc, 2003 Table of Content I: METHODOLOGIES OF DATA MINING 1 Decision Trees 2 Association Rules 3 Artificial Neural Network Models for Data Mining 4 Statistical Analysis of Normal and Abnormal Data 5 Bayesian Data Analysis 6 Hidden Markov Processes and Sequential Pattern Mining 7 Strategies and Methods for Prediction 8 Principal Components and Factor Analysis 9 Psychometric Methods of Latent Variable Modeling 10 Scalable Clustering 11 Time Series Similarity and Indexing 12 Nonlinear Time Series Analysis 13 Distributed Data Mining II: MANAGEMENT OF DATA MINING 14 Data Collection, Preparation, Quality, and Visualization 15 Data Storage and Management 16 Feature Extraction, Selection, and Construction 17 Performance Analysis and Evaluation 18 Security and Privacy 19 Emerging Standards and Interfaces 20 Mining Human Performance Data 21 Mining Text Data 22 Mining Geospatial Data 23 Mining Science and Engineering Data 24 Mining Data in Bioinformatics 25 Mining Customer Relationship Management (CRM) Data 26 Mining Computer and Network Security Data 27 Mining Image Data 28 Mining Manufacturing Quality Data