Howard J. Hamilton

7. Geng, L. and Hamilton, H.J.,
``Choosing the Right Lens: Finding What is Interesting in Data Mining,'' In F. Guillet and H. J. Hamilton (eds.), Quality Measures in Data Mining, Springer, Berlin, 3-24, 2007.

6. Yao, H., Butz, C.J., and Hamilton, H.J.,
``Causal Discovery,'' In O. Maimon and L. Rokach (eds.), The Data Mining and Knowledge Discovery Handbook, Springer, Berlin, 945-955, 2005.
http://www.informatik.uni-trier.de/~ley/db/books/collections/datamining2005.html

5. Geng, L., and Hamilton, H.J.,
``Automated Case Generation from Databases Using Similarity-Based Rough Approximation,'' In Abraham, A., Jain, L.C., and Zwaag, B.J.v.d. (eds.), Innovations in Intelligent Systems: Design, Management and Applications, Springer, Berlin, January, 2004, ISBN: 3-540-20265-X.

4. Hamilton, H.J., and Randall, D.J.
``Data Mining with Calendar Attributes,'' In Hornsby, K., and Roddick, J. (eds.), Temporal, Spatial, and Spatio-Temporal Data Mining, Springer-Verlag, Berlin, 2001, pp. 117-132.

3. Hilderman, R.J., Li, L., and Hamilton, H.J.
"Data Visualization for Data Mining with Domain Generalization Graphs," In Fayyad, U., Grinstein, G.G., and Wierse, A., (eds.), Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann, 2001, pp. 251-270.

2. Cercone, N., Hamilton, H., Hu, X., and Shan, N.
"Data Mining Using Attribute-Oriented Generalization and Information Reduction," in Lin, T.Y. and Cercone, N., Rough Sets and Data Mining: Analysis for Imprecise Data, Kluwer, 1997, pp. 199-227.

1. Fudger, D.F. and Hamilton, H.J.
"A Heuristic for Evaluating Databases for Knowledge Discovery with DBLEARN," in Ziarko, W. (ed.), Rough Sets, Fuzzy Sets and Knowledge Discovery, Springer-Verlag, New York, 1994, pp. 44-51.