Data mining : concepts and techniques
Author(s)
Bibliographic Information
Data mining : concepts and techniques
(The Morgan Kaufmann series in data management systems)
Morgan Kaufmann, c2012
3rd ed
Available at 45 libraries
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Note
Includes bibliographical references (p. 633-671) and index
Description and Table of Contents
Description
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.
This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.
Table of Contents
1. Introduction2. Getting to Know Your Data3. Preprocessing: Data Reduction, Transformation, and Integration4. Data Warehousing and On-Line Analytical Processing5. Data Cube Technology 6. Mining Frequent Patterns, Associations and Correlations: Concepts and Methods7. Advanced Frequent Pattern Mining8. Classification: Basic Concepts9. Classification: Advanced Methods10. Cluster Analysis: Basic Concepts and Methods11. Cluster Analysis: Advanced Methods12. Outlier Analysis13. Trends and Research Frontiers in Data Mining
by "Nielsen BookData"