Data mining carries some very specific connotations (e.g., massive data sets). which I am not adhering to here. There is certainly data mining relevance in each of the following, however, each of which appear in data mining or data analysis conferences. See also Rule based learning journal publications and Conceptual Clustering publications.

Fisher, D. (1995). "Optimization and Simplification of Hierarchical Clusterings," First International Conference on Knowledge Discovery in Databases, Montreal, Canada: AAAI Press, 118--123.

Frey, L., & Fisher, D. (1999). "Modeling Decision Tree Performance with the Power Law" Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, Ft. Lauderdale, FL: Morgan Kaufmann, 59--65.

Talbert, D., & Fisher, D. (1999). "Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with KD-Trees," Advances in Intelligent Data Analysis, Lecture Notes on Computer Science No. 1642 (Third International Symposium on Intelligent Data Analysis), Amsterdam, Netherlands: Springer, 407--414.

Talbert, D. & Fisher, D. (2000). "An Empirical Analysis of Techniques for Constructing and Searching K-Dimensional Trees," Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining, AAAI Press, 26--33.

Frey, L., Fisher, D., Tsamardinos, I., Aliferis, C., & Statnikov, A. (2003). "Identifying Markov Blankets with Decision Tree Induction," Third IEEE International Conference on Data Mining, Melbourne, FL, 59-66.

Waitman, L. R., Fisher, D., & King, P. H. (2003). "Bootstrapping rule induction," Third IEEE International Conference on Data Mining, Melbourne, FL, 677-680.

Fisher, D., Edgerton, M., Tang, L., Frey, L., & Chen, Z. (2005). "Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction," Advances in Intelligent Data Analysis VI, Lecture Notes on Computer Science No. 3646 (Sixth Biennial Conference on Intelligent Data Analysis), Madrid, Spain: Springer, 86--96.