Jiawei Han, Jian Pei, Hanghang Tong

Data Mining (eBook, ePUB)

Concepts and Techniques

• Format: ePub

Produktbeschreibung

Data Mining: Concepts and Techniques, Fourth Edition provides the theories and methods for processing data or information used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from collected data, known as KDD. The book focuses on the feasibility, usefulness, effectiveness and scalability of techniques of large datasets. After describing data mining, the authors explain the methods of knowing, preprocessing, processing and warehousing data. They then present 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. Users from computer science students, application developers, business professionals, and researchers who seek information on data mining will find this resource very helpful.

• 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 needed to get the most out of your data

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 752
• Erscheinungstermin: 2. Juli 2022
• Englisch
• ISBN-13: 9780128117613
• Artikelnr.: 64270526

Autorenporträt

Jiawei Han is Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Well known for his research in the areas of data mining and database systems, he has received many awards for his contributions in the field, including the 2004 ACM SIGKDD Innovations Award. He has served as Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data, and on editorial boards of several journals, including IEEE Transactions on Knowledge and Data Engineering and Data Mining and Knowledge Discovery.

Inhaltsangabe

1. Introduction
2. Data, measurements, and data processing
3. Data warehousing and online analytical processing
4. Pattern mining: basic concepts and methods
5. Pattern mining: advanced methods
6. Classification: basic concepts and methods
7. Classification: advanced methods
8. Cluster analysis: basic concepts and methods
9. Cluster analysis: advanced methods
10. Deep learning
11. Outlier Detection
12. Data mining trends and research frontiers
Appendix: Mathematical background