Ye N. (ed.) The Handbook of Data Mining

Mahwah: Lawrence Erlbaum Associates, 2003. — 689 p. — (Human Factors and Ergonomics). — ISBN: 0-8058-4081-8.Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials.
This book is organized into three parts. Part I presents various data mining methodologies, concepts, and available software tools for each methodology. Part II addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. Part III features numerous real-world applications of these techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, and manufacturing quality.
This Handbook is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. It is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.Methodologies of Data Mining
Decision Trees
Association Rules
Artificial Neural Network Models for Data Mining
Statistical Analysis of Normal and Abnormal Data
Bayesian Data Analysis
Hidden Markov Processes and Sequential Pattern Mining
Strategies and Methods for Prediction
Principal Components and Factor Analysis
Psychometric Methods of Latent Variable Modeling
Scalable Clustering
Time Series Similarity and Indexing
Nonlinear Time Series Analysis
Distributed Data Mining
Management of Data Mining
Data Collection, Preparation, Quality, and Visualization
Data Storage and Management
Feature Extraction, Selection, and Construction
Performance Analysis and Evaluation
Security and Privacy
Emerging Standards and Interfaces
Applications of Data Mining
Mining Human Performance Data
Mining Text Data
Mining Geospatial Data
Mining Science and Engineering Data
Mining Data in Bioinformatics
Mining Customer Relationship Management (CRM) Data
Mining Computer and Network Security Data
Mining Image Data
Mining Manufacturing Quality Data