Data Mining Concepts and Techniques

Jiawei Han 지음

elsevier 2011년 06월 09일 출간

작품소개

책소개

The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it？？s still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the previous edition？？s publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today？？s most powerful data mining techniques to meet real business challenges. * 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

목차

Chapter 1. Introduction Chapter 2. Getting to Know Your Data Chapter 3. Preprocessing Chapter 4. Data Warehousing and On-Line Analytical Processing Chapter 5. Data Cube Technology Chapter 6. Mining Frequent Patterns, Associations and Correlations: Concepts and Methods Chapter 7. Advanced Frequent Pattern Mining Chapter 8. Classification: Basic Concepts Chapter 9. Classification: Advanced Methods Chapter 10. Cluster Analysis: Basic Concepts and Methods Chapter 11. Advanced Cluster Analysis Chapter 12. Outlier Analysis Chapter 13. Data Mining Trends and Research Frontiers in Data Mining

출판사 서평

"[A] well-written textbook (2nd ed., 2006; 1st ed., 2001) on data mining or knowledge discovery. The text is supported by a strong outline. The authors preserve much of the introductory material, but add the latest techniques and developments in data mining, thus making this a comprehensive resource for both beginners and practitioners. The focus is data-all aspects. The presentation is broad, encyclopedic, and comprehensive, with ample references for interested readers to pursue in-depth research on any technique. Summing Up: Highly recommended. Upper-division undergraduates through professionals/practitioners."--CHOICE "This interesting and comprehensive introduction to data mining emphasizes the interest in multidimensional data mining--the integration of online analytical processing (OLAP) and data mining. Some chapters cover basic methods, and others focus on advanced techniques. The structure, along with the didactic presentation, makes the book suitable for both beginners and specialized readers."--ACM？？s Computing Reviews.com We are living in the data deluge age. The Data Mining: Concepts and Techniques shows us how to find useful knowledge in all that data. Thise 3rd editionThird Edition significantly expands the core chapters on data preprocessing, frequent pattern mining, classification, and clustering. The bookIt also comprehensively covers OLAP and outlier detection, and examines mining networks, complex data types, and important application areas. The book, with its companion website, would make a great textbook for analytics, data mining, and knowledge discovery courses.--Gregory Piatetsky, President, KDnuggets Jiawei, Micheline, and Jian give an encyclopaedic coverage of all the related methods, from the classic topics of clustering and classification, to database methods (association rules, data cubes) to more recent and advanced topics (SVD/PCA , wavelets, support vector machines)？？ Overall, i

작가정보

저자(글) Jiawei Han