Chapter 8. Data Mining for Business and Industry
- Shirley Coleman Technical Director2,
- Tony Greenfield3,
- Dave Stewardson2,
- Douglas C. Montgomery4
Published Online: 3 MAR 2008
DOI: 10.1002/9780470997482.ch8
Copyright © 2008 John Wiley & Sons, Ltd
Book Title
Statistical Practice in Business and Industry
Additional Information
How to Cite
Cerchiello, P., Figini, S. and Giudici, P. (2008) Data Mining for Business and Industry, in Statistical Practice in Business and Industry (eds S. Coleman, T. Greenfield, D. Stewardson and D. C. Montgomery), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470997482.ch8
Editor Information
- 2
Industrial Statistics Research Unit, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
- 3
Greenfield Research, Little Hucklow, Buxton SK17 8RT, UK
- 4
Regents' Professor of Industrial Engineering & Statistics, ASU Foundation Professor of Engineering, Department of Industrial Engineering Arizona State University Tempe, AZ 85287-5906, USA
Publication History
- Published Online: 3 MAR 2008
- Published Print: 7 MAR 2008
Book Series:
ISBN Information
Print ISBN: 9780470014974
Online ISBN: 9780470997482
- Summary
- Chapter
Keywords:
- data mining - selection, exploration, and modelling;
- data mining - data analysis process;
- neural networks (multilayer perceptrons) and decision trees;
- data mining applications;
- web usage mining;
- customer relationship management;
- credit scoring and creditworthiness;
- non-inferential and inferential models;
- inferential models and web mining pattern discovery;
- text mining and text mining technologies
Summary
This chapter contains sections titled:
What is data mining?
Data mining methods
Data mining applications
A case study in web usage mining
A case study in text mining
Results and conclusions
References