Data mining techniques : for marketing, sales, and customer support / Michael J.A. Berry and Gordon Linoff.
By: Berry, Michael J. A.
Contributor(s): Linoff, Gordon.Material type: TextPublisher: New York : Wiley, c1997Description: x, 454 p. : ill. ; 24 cm.ISBN: 0471179809 (pbk. : alk. paper); 9780471179801.Subject(s): Data mining | Marketing -- Data processing | Business -- Data processingDDC classification: 005.7 Online resources: WorldCat Details | Ebook Fulltext
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|E-Book||EWU Library E-book||Non-fiction||005.7 BED 1997 (Browse shelf)||Not for loan|
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Includes bibliographical references (p. 443-444) and index.
1. Why Data Mining? --
2. Virtuous Cycle of Data Mining --
3. Virtuous Cycle in Practice --
4. What Can Data Mining Do? --
5. Data Mining Methodology --
6. Measuring the Effectiveness of Data Mining --
7. Overview of Data Mining Techniques --
8. Market Basket Analysis --
9. Memory-Based Reasoning --
10. Automatic Cluster Detection --
11. Link Analysis --
12. Decision Trees --
13. Artificial Neural Networks --
14. Genetic Algorithms --
15. Data Mining and the Corporate Data Warehouse --
16. Where Does OLAP Fit In? --
17. Choosing the Right Tool for the Job --
18. Putting Data Mining to Work.
"Data Mining Techniques thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions. One of the first practical guides to mining business data, it describes techniques for detecting customer behavior patterns useful in formulating marketing, sales, and customer support strategies. While database analysts will find more than enough technical information to satisfy their curiosity, technically savvy business and marketing managers will find the coverage eminently accessible. Here's your chance to learn all about how leading companies across North America are using data mining to beat the competition; how each tool works, and how to pick the right one for the job; seven powerful techniques - cluster detection, memory-based reasoning, market basket analysis, genetic algorithms, link analysis, decision trees, and neural nets, and how to prepare data sources for data mining, and how to evaluate and use the results you get." "Data Mining Techniques shows you how to quickly and easily tap the gold mine of business solutions lying dormant in your information systems."--Jacket.
Computer Science & Engineering