Data Mining: Introductory and Advanced Topics (Paperback)
  • Data Mining: Introductory and Advanced Topics (Paperback)

Data Mining: Introductory and Advanced Topics (Paperback)

Paperback 336 Pages / Published: 13/09/2002
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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

Publisher: Pearson Education (US)
ISBN: 9780130888921
Number of pages: 336
Weight: 640 g
Dimensions: 242 x 182 x 18 mm


"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

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