Data Mining: Introductory and Advanced Topics

"It is the best book on data mining so far, and I would definitely adopt it for my course. The book is very comprehensive and covers all of the data mining topics and algorithms of which 1 am aware. The depth of coverage of each topic or method is exactly right and appropriate. Each algorithm is presented in pseudocode that is sufficient for any interested readers to convert into a working implementation in a computer language of their choice." - Michael H. Huhns, University of South Carolina "Discussion on distributed, parallel, and incremental algorithms is outstanding." - Zoran Obradovic, Temple University

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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