Contents.

Introduction. -- Getting to Know Your Data. -- Data Preprocessing. -- Data Warehousing and Online Analytical Processing. -- Data Cube Technology. -- Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods. -- Advanced Pattern Mining. -- Classification: Basic Concepts. -- Classification: Advanced Methods. -- Cluster Analysis: Basic Concepts and Methods. -- Advanced Cluster Analysis. -- Outlier Detection. -- Data Mining Trends and Research Frontiers.

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining.