Data mining : concepts and techniques

Han, Jiawei. (Author). Kamber, Micheline. (Added Author). Pei, Jian (Computer scientist) (Added Author).

Summary: 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. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data.

Record details

ISBN: 6613171174
ISBN: 9786613171177
ISBN: 9781283171175
ISBN: 1283171171
ISBN: 9780123814791
ISBN: 0123814804
ISBN: 9780123814807
ISBN: 9780123814791
ISBN: 0123814790
Physical Description: 1 online resource (xxxv, 703 pages) : illustrations, facsimiles.
remote
Edition: 3rd ed.
Publisher: Waltham, MA : Morgan Kaufmann/Elsevier, ©2012.

Content descriptions

Bibliography, etc. Note:	Includes bibliographical references (pages 633-671) and index.
Formatted Contents Note:	12.2 Outlier Detection Methods -- 12.3 Statistical Approaches -- 12.4 Proximity-Based Approaches -- 12.5 Clustering-Based Approaches -- 12.6 Classification-Based Approaches -- 12.7 Mining Contextual and Collective Outliers -- 12.8 Outlier Detection in High-Dimensional Data -- 12.9 Summary -- 12.10 Exercises -- 12.11 Bibliographic Notes -- Chapter 13. Data Mining Trends and Research Frontiers -- 13.1 Mining Complex Data Types -- 13.2 Other Methodologies of Data Mining -- 13.3 Data Mining Applications -- 13.4 Data Mining and Society -- 13.5 Data Mining Trends -- 13.6 Summary -- 13.7 Exercises -- 13.8 Bibliographic Notes -- Bibliography -- Index.
Language Note:	English.
Source of Description Note:	Print version record.