Books

Claude C. Hopkins, My Life in Advertising and Scientific Advertisiing, NTC Business Books, Chicago, 1996, orginally published, 1923 and 1927 respectively - two classics about advertising.

Arthur M. Hughes, Strategic Database Marketing, Irwin, Burr Ridge, Illinois, 1994 - a practical introduction to database marketing.

Leo Breiman, Jerome H. Friedman, Richard A. Olshen, and Charles J. Stone, Classification and Regression Trees, Chapman & Hall, New York, 1984. - A classic introduction to trees and their applications to classification and prediction.

Michael J. A. Berry and Gordon Linoff, Data Mining Tehniques for Marketing, Sales, and Customer Support, John Wiley and Sons, New York, NY, 1997.

Michael J. A. Berry and Gordon Linoff, Mastering Data Mining, John Wiley & Sons, New York, 2000 - practical advice about data mining.

Tom M. Mitchell, Machine Learning, WCB McGraw-Hill, Boston, 1997 - a concise introduction to machine learning from the AI perspective.

Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, San Francisco, 2001 - a good introduction to data mining from the systems and database perspective.

David Hand, Heikki Mannila and Padhraic Smyth, Principles of Data Mining, MIT Press, Cambridge, Massachusetts, 2001 - a text book written by three experts in the field.

Ian H. Witten and Eibe Frank, Data Mining, Morgan Kaufmann Publishers, San Francisco, 2000 - a good introduction which includes Java tools for the common algorithms.

Luc Devroye, Laszlo Gyorfi, Gabor Lugosi, A Probabilistic Theory of Pattern Recognition, Springer-Verlag, New York, 1996 - proves probabilistic error estimates for many of the common data mining algorithms.

Nello Cristianini and John Shawe-Taylor, An Introduction to Support Vector Machines, Springer-Verlag, New York, 2000 - one of the first books on support vector machines, which are emerging as a powerful data mining technique.
Trevor Hastie, Robert Tibshirani, and Jerome Friedman, The Elements of Statistical Learning, Springer-Verlag, New York, 2001 - data mining algorithms from a statistical point of view.
Vladimir N. Vapnik, The Nature of Statistical Learning Theory, Second Edition, Springer-Verlag, 2000 - an influential technical book covering theoretical aspects of learning.
Ian H. Witten, Alistair Moffat and Timothy C. Bell, Managing Gigabytes, Second Edition, Morgan Kaufmann, San Diego, 1999 - a good book describing the infrastructurre and theory required for working with large collections of text or images.
Michael W. Berry and Murray Browne, Understanding Search Engines, SIAM, Philadelphia, 1999 - a quick introduction to search engines, including some of the underlying linear algebra required.

Robert Grossman