Data Mining: Concepts and Techniques / Edition 3
by Jiawei Han, Micheline Kamber, Jian Pei
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
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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 thisThird Editionof 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.
Product Details
- ISBN-13:
- 9780123814791
- Publisher:
- Elsevier Science
- Publication date:
- 07/06/2011
- Series:
- Morgan Kaufmann Series in Data Management Systems Series
- Pages:
- 744
- Sales rank:
- 433,390
- Product dimensions:
- 7.80(w) x 9.30(h) x 1.70(d)
Table of Contents
| Ch. 1 | Introduction | 1 |
| Ch. 2 | Data preprocessing | 47 |
| Ch. 3 | Data warehouse and OLAP technology : an overview | 105 |
| Ch. 4 | Data cube computation and data generalization | 157 |
| Ch. 5 | Mining frequent patterns, associations, and correlations | 227 |
| Ch. 6 | Classification and prediction | 285 |
| Ch. 7 | Cluster analysis | 383 |
| Ch. 8 | Mining stream, time-series, and sequence data | 467 |
| Ch. 9 | Graph mining, social network analysis, and multirelational data mining | 535 |
| Ch. 10 | Mining object, spatial, multimedia, text, and Web data | 591 |
| Ch. 11 | Applications and trends in data mining | 649 |
| App | An introduction to Microsoft's OLE DB for data mining | 691 |
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