Data Mining

Data Mining : Introductory and Advanced Topics

4.17 (63 ratings by Goodreads)
By (author) 

Free delivery worldwide

Available. Dispatched from the UK in 3 business days
When will my order arrive?

Description

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 productsshow more

Product details

  • Paperback | 315 pages
  • 177.8 x 231.14 x 22.86mm | 544.31g
  • Pearson Education (US)
  • Prentice Hall
  • Upper Saddle River, United States
  • English
  • 0130888923
  • 9780130888921
  • 1,997,988

Review quote

"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 Universityshow more

About Margaret H. Dunham

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.show more

Back cover copy

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 productsshow more

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.show more

Rating details

63 ratings
4.17 out of 5 stars
5 43% (27)
4 38% (24)
3 14% (9)
2 3% (2)
1 2% (1)
Book ratings by Goodreads
Goodreads is the world's largest site for readers with over 50 million reviews. We're featuring millions of their reader ratings on our book pages to help you find your new favourite book. Close X