Synopsis
Thorough in its coverage from basic to advanced topics, this book presents the key algorithms and techniques used in data mining. An emphasis is placed on the use of data mining concepts in real world applications with large database components. Includes unique chapters on Web mining, spatial mining, temporal mining, and prototypes and DM products. Separate case studies section highlights real world applications. An excellent reference book for computer database professionals and researchers.
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About the Author
Margaret H. Dunham received the B.A. and the M.S. in mathematics from Miami University in Oxford, Ohio. She earned the Ph.D. degree in computer science from Southern Methodist University. Professor Dunham's research interests encompass main memory databases, data mining, temporal databases, and mobile computing. She is currently an Associate Editor for IEEE Transactions on Knowledge and Data Engineering. She has published numerous technical papers in such research areas as database concurrency control and recovery, database machines, main memory databases, and mobile computing.
From the Back Cover
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
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Data Mining: Introductory and Advanced Topics
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