Books

Bezdek, J. C., & Pal, S. K. (1992). Fuzzy models for pattern recognition: Methods that search for structures in data. New York: IEEE Press

Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., & Uthurusamy, R. (Eds.). (1996). Advances in knowledge discovery and data mining. AAAI/MIT Press.

Han, J., & Kamber, M. (2000). Data mining: Concepts and techniques: Morgan Kaufmann.

Hastie, T., Tibshirani, R., & Friedman, J. H. (2001). The elements of statistical learning: Data mining, inference, and prediction: New York: Springer.

Jain, A. K., & Dubes, R. C. (1988). Algorithms for clustering data. New Jersey: Prentice Hall.

Jensen, F. V. (1996). An introduction to bayesian networks. London: University College London Press.

Kaufman, L., & Rousseeuw, P. J. (1990). Finding groups in data: An introduction to cluster analysis. New York: John Wiley.

Michie, D., Spiegelhalter, D. J., & Taylor, C. C. (1994). Machine learning, neural and statistical classification: Ellis Horwood.

Articles

Agrawal, R., Imieliski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data. Washington, D.C., United States: ACM Press.

Bauer, E., & Kohavi, R. (1999). An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 36(1 - 2), 105.

Bittner, T. (2001). Rough sets in spatio-temporal data mining, Proceedings of the First International Workshop on Temporal, Spatial, and Spatio-Temporal Data Mining-Revised Papers: Springer-Verlag.

Chakrabarti, S., Dom, B. E., Kumar, S. R., Raghavan, P., Rajagopalan, S., Tomkins, A., et al. (1999). Mining the web's link structure. Computer, 32(8), 60-67.

Cheeseman, P., & Stutz, J. (1996). Bayesian classification (autoclass): Theory and results. In Advances in knowledge discovery and data mining (pp. 153-180): American Association for Artificial Intelligence.

Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391-407.

Elias, B. (2003). Extracting landmarks with data mining methods. In W. Kuhn, M. Worboys & S. Timpf (Eds.), Spatial information theory: Foundations of geographic information science; (International Conference, COSIT 2003, Kartause Ittingen, Switzerland ed., pp. 375-389): Springer-Verlag.

Ferreira de Oliveira, M. C., & Levkowitz, H. (2003). From visual data exploration to visual data mining: A survey. Visualization and Computer Graphics, IEEE Transactions on, 9(3), 378.

Han, J., Altman, R. B., Kumar, V., Mannila, H., & Pregibon, D. (2002). Emerging scientific applications in data mining. Commun. ACM, 45(8), 54-58.

Imielinski, T., & Mannila, H. (1996). A database perspective on knowledge discovery. Commun. ACM, 39(11), 58-64.

Jinwook, S., & Shneiderman, B. (2002). Interactively exploring hierarchical clustering results [gene identification]. Computer, 35(7), 80.

Kohonen, T. (1982). Analysis of a simple self-organizing process. Biological Cybernetics (Historical Archive), 44(2), 135.

Lagus, K., Honkela, T., Kaski, S., & Kohonen, T. (1999). Websom for textual data mining. Artificial Intelligence Review, 13(5 - 6), 345.

Milligan, G. W., & Hirtle, S. C. (2003). Clustering and classification methods. In J. Schinka & W. Velicer (Eds.), Comprehensive handbook of psychology (Vol. 2, pp. 165-186). New York: Wiley.

Mitra, S., Pal, S. K., & Mitra, P. (2002). Data mining in soft computing framework: A survey. Neural Networks, IEEE Transactions on, 13(1), 3.

Ng, R. T., & Han, J. (2002). Clarans: A method for clustering objects for spatial data mining. Knowledge and Data Engineering, IEEE Transactions on, 14(5), 1003.

Nigam, K., McCallum, A., Thrun, S., & Mitchell, T. (1998). Learning to classify text from labeled and unlabeled documents, Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence. Madison, Wisconsin, United States: American Association for Artificial Intelligence.

Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1(1), 81-106.

Ramaswamy, S., Mahajan, S., & Silberschatz, A. (1998). On the discovery of interesting patterns in association rules, Proceedings of the 24th International Conference on Very Large Data Bases: Morgan Kaufmann.

Rumelhart, D. E., & Zipser, D. (1985). Feature discovery by competitive learning. Cognitive Science, 9, 75-112.

Thrun, S. (1998). Bayesian landmark learning for mobile robot localization. Mach. Learn., 33(1), 41-76.