Features
- A database perspective is used throughout.
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Provides students with a focused discussion of algorithms, data structures, data types, and complexity of algorithms and space.
- Clearly written algorithms.
- An emphasis on the use of data mining concepts in real-world applications with large database components.
- Appendix providing overview of available data mining products.
- Strategic text organisation of four major sections: Introduction, Core Topics, Advanced Topics, and Products.
- Copyright 2003
- Dimensions: 7" x 9-1/4"
- Pages: 336
- Edition: 1st
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Book
- ISBN-10: 0-13-088892-3
- ISBN-13: 978-0-13-088892-1
Margaret Dunham offers the experienced data base professional or graduate level Computer Science student an introduction to the full spectrum of Data Mining concepts and algorithms. Using a database perspective throughout, Professor Dunham examines algorithms, data structures, data types, and complexity of algorithms and space. This text emphasizes the use of data mining concepts in real-world applications with large database components.
KEY FEATURES: - Covers advanced topics such as Web Mining and Spatial/Temporal mining
- Includes succinct coverage of Data Warehousing, OLAP, Multidimensional Data, and Preprocessing
- Provides case studies
- Offers clearly written algorithms to better understand techniques
- Includes a reference on how to use Prototypes and DM products
Table of Contents
- I. INTRODUCTION.
- 1. Introduction.
- 2. Related Concepts.
- 3. Data Mining Techniques.
- II. CORE TOPICS.
- 4. Classification.
- 5. Clustering.
- 6. Association Rules.
- III. ADVANCED TOPICS.
- 7. Web Mining.
- 8. Spatial Mining.
- 9. Temporal Mining.
- IV. APPENDIX.
- 10. Data Mining Products.