Sumathi S., Sivanandam S.N. Introduction to Data Mining and its Applications

Springer, 2006. — 828 p. — ISBN: 3540343504, 978-3540343509.This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.Introduction to Data Mining Principles
Data Warehousing, Data Mining, and OLAP
Data Marts and Data Warehouse
Evolution and Scaling of Data Mining Algorithms
Emerging Trends and Applications of Data Mining
Data Mining Trends and Knowledge Discovery
Data Mining Tasks, Techniques, and Applications
Data Mining: an Introduction – Case Study
Data Mining & KDD
Statistical Themes and Lessons for Data Mining
Theoretical Frameworks for Data Mining
Major and Privacy Issues in Data Mining and Knowledge Discovery
Active Data Mining
Decomposition in Data Mining - A Case Study
Data Mining System Products and Research Prototypes
Data Mining in Customer Value and Customer Relationship Management
Data Mining in Business
Data Mining in Sales Marketing and Finance
Banking and Commercial Applications
Data Mining for Insurance
Data Mining in Biomedicine and Science
Text and Web Mining
Data Mining in Information Analysis and Delivery
Data Mining in Telecommunications and Control
Data Mining in Security
Data Mining Research Projects
Data Mining Standards
Intelligent Miner
Clementine
Crisp
Mineset
Enterprise Miner