Textbook and Materials

Because Data Mining is a new and evolving topic, no single textbook adequately covers all of the pertinent topics. As a result, the materials for this class will consist of research papers. The paper to be covered each class period is listed on the class home page at http://www-cse.uta.edu/$\sim$cook/dm. Links are provided to papers that can be obtained electronically. Copies of all other required papers papers will be available on reserve in the Engineering Library.

Although no text book is required, I strongly suggest obtaining a copy of the Advances in Knowledge Discovery and Data Mining book edited by Fayyad et al. This book covers many of the major Data Mining topics, and is listed as alternative reading to the online papers for many of the classes.

Additional books that may be of use during the semester include:

• T. Mitchell, Machine Learning, McGraw-Hill, 1997.
• S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall, 1995.
• S. Weiss and N. Indurkhya, Predictive Data Mining: A Practical Guide, Morgan Kaufmann, 1997.
• A. Berson and S. Smith, Data Warehousing, Data Mining, and OLAP, McGraw-Hill, 1997.