Data Mining by Mehmed Kantardzic (inspirational novels TXT) 📗

Measures for Categorical Data: A Comparative Evaluation, SIAM Conference, 2008, pp. 243–254.

Bow, S., Pattern Recognition and Image Preprocessing, Marcel Dekker, New York, 1992.

Chen, C. H., L. F. Pau, P. S. P. Wang, Handbook of Pattern Recognition & Computer Vision, World Scientific Publ. Co., Singapore, 1993.

Dzeroski, S., N. Lavrac, eds., Relational Data Mining, Springer, Berlin, 2001.

Gose, E., R. Johnsonbaugh, S. Jost, Pattern Recognition and Image Analysis, Prentice Hall, Inc., Upper Saddle River, NJ, 1996.

Han, J., M. Kamber, Data Mining: Concepts and Techniques, 2nd edition, Elsevier Inc., San Francisco, CA, 2006.

Han, J., et al., Spatial Clustering Methods in Data Mining: A Survey, in Geographic Data Mining and Knowledge Discovery, H. Miller, J. Han, eds., Taylor & Francis Publ. Inc., London, 2001.

Hand, D., H. Mannila, P. Smyth, Principles of Data Mining, The MIT Press, Cambridge, MA, 2001.

Jain, A. K., Data Clustering: 50 Years Beyond K-Means, Pattern Recognition Letters, Vol. 31, No. 8, 2010, pp. 651–666.

Jain, A. K., M. N. Murty, P. J. Flynn, Data Clustering: A Review, ACM Computing Surveys, Vol. 31, No. 3, 1999, pp. 264–323.

Jin, H., H. Shum, K. Leung, M. Wong, Expanding Self-Organizing Map for Data Visualization and Cluster Analysis, Information Sciences, Vol. 163, Nos. 1–3, 2004, pp. 157–173.

Karypis, G., E. Han, V. Kumar, Chameleon: Hierarchical Clustering Using Dynamic Modeling, Computer, Vol. 32, No. 8, 1999, pp. 68–75.

Lee, I., J. Yang, Common Clustering Algorithms, Comprehensive Chemometrics, 2009, Chapter 2.27, pp. 577–618.

Moore, S. K., Understanding the Human Genoma, Spectrum, Vol. 37, No. 11, 2000, pp. 33–35.

Munakata, T., Fundamentals of the New Artificial Intelligence: Beyond Traditional Paradigm, Springer, New York, 1998.

Norusis, M. J., SPSS 7.5: Guide to Data Analysis, Prentice-Hall, Inc., Upper Saddle River, NJ, 1997.

Poole, D., A. Mackworth, R. Goebel, Computational Intelligence: A Logical Approach, Oxford University Press, Inc., New York, 1998.

Tan, P.-N., M. Steinbach, V. Kumar, Introduction to Data Mining, Pearson Addison-Wesley, Boston, 2006.

Westphal, C., T. Blaxton, Data Mining Solutions: Methods and Tools for Solving Real-World Problems, John Wiley & Sons, Inc., New York, 1998.

Witten, I. H., E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmannn Publ., Inc., New York, 1999.

CHAPTER 10

Adamo, J., Data Mining for Association Rules and Sequential Patterns, Springer, New York, 2001.

Beyer, K., R. Ramakrishnan, Bottom-Up Computation of Sparse and Iceberg Cubes, Proceedings of 1999 ACM-SIGMOD Int. Conf. on Management of Data (SIGMOD’99), Philadelphia, PA, June, 1999, pp. 359–370.

Bollacker, K. D., S. Lawrence, C. L. Giles, Discovering Relevant Scientific Literature on the Web, IEEE Intelligent Systems, March/April 2000, pp. 42–47.

Chakrabarti, S., Data Mining for Hypertext: A Tutorial Survey, SIGKDD Explorations, Vol. 1, No. 2, 2000, pp. 1–11.

Chakrabarti, S., et al., Mining the Web’s Link Structure, Computer, Vol. 32, No. 8, 1999, pp. 60–67.

Chang, G., M. J. Haeley, J. A. M. McHugh, J. T. L. Wang, Mining the World Wide Web: An Information Search Approach, Kluwer Academic Publishers, Boston, MA, 2001.

Chen, M., J. Park, P. S. Yu, Efficient Data Mining for Path Traversal Patterns, IEEE Transactions on Knowledge and Data Engineering, Vol. 10, No. 2, 1998, pp. 209–214.

Cios, K. J., W. Pedrycz, R. W. Swiniarski, L. A. Kurgan, Data Mining: A Knowledge Discovery Approach, Springer, New York, 2007.

Cromp, R. F., W. J. Campbell, Data Mining of Multidimensional Remotely Sansad Images, Proceedings of the CIKM’93 Conference, Washington, DC, 1993, pp. 471–480.

Darlington, J., Y. Guo, J. Sutiwaraphun, H. W. To, Parallel Induction Algorithms for Data Mining, Proceedings of the Third International Conference on Knowledge Discovery and Data Mining KDD’97, 1997, pp. 35–43.

Fayyad, U. M., G. Piatetsky-Shapiro, P. Smith, R. Uthurusamy, eds., Advances in Knowledge Discovery and Data Mining, AAAI Press/MIT Press, Cambridge, 1996.

Fukada, T., Y. Morimoto, S. Morishita, T. Tokuyama, Data Mining Using Two-Dimensional Optimized Association Rules: Scheme, Algorithms, and Visualization, Proceedings of SIGMOD’96 Conference, Montreal, 1996, pp. 13–23.

Han, J., Towards On-Line Analytical Mining in Large Databases, SIGMOD Record, Vol. 27, No. 1, 1998, pp. 97–107.

Han, J., M. Kamber, Data Mining: Concepts and Techniques, 2nd edition, Elsevier Inc., San Francisco, CA, 2006.

Han, J., J. Pei, Mining Frequent Patterns by Pattern-Growth: Methodology and Implications, SIGKDD Explorations, Vol. 2, No. 2, 2000, pp. 14–20.

Han, E., G. Karypis, V. Kumar, Scalable Parallel Data Mining for Association Rules, Proceedings of the SIGMOD’97 Conference, Tucson, 1997a, pp. 277–288.

Han, J., K. Koperski, N. Stefanovic, GeoMiner: A System Prototype for Spatial Data Mining, Proceedings of the SIGMOD’97 Conference, Arizona, 1997b, pp. 553–556.

Han, J., S. Nishio, H. Kawano, W. Wang, Generalization-Based Data Mining in Object-Oriented Databases Using an Object Cube Model, Proceedings of the CASCON’97 Conference, Toronto, November 1997c, pp. 221–252.

Hedberg, S. R., Data Mining Takes Off at the Speed of the Web, IEEE Intelligent Systems, November/December 1999, pp. 35–37.

Hilderman, R. J., H. J. Hamilton, Knowledge Discovery and Measures of Interest, Kluwer Academic Publishers, Boston, MA, 2001.

Integral Solutions, 1999, Clementine, http://www.isl.co.uk/clem.html.

Kasif, S., Datascope: Mining Biological Sequences, IEEE Intelligent Systems, November/December 1999, pp. 38–43.

Kosala, R., H. Blockeel, Web Mining Research: A Survey, SIGKDD Explorations, Vol. 2, No. 1, 2000, pp. 1–15.

Kowalski, G. J., M. T. Maybury, Information Storage and Retrieval Systems: Theory and Implementation, Kluwer Academic Publishers, Boston, 2000.

Liu, B., W. Hsu, L. Mun, H. Lee, Finding Interesting Patterns Using User Expectations, IEEE Transactions on Knowledge and Data Engineering, Vol. 11, No. 6, 1999, pp. 817–825.

McCarthy, J., Phenomenal Data Mining, CACM, Vol. 43, No. 8, 2000, pp. 75–79.

Moore, S. K., Understanding the Human Genome, Spectrum, Vol. 37, No. 11, 2000, pp. 33–35.

Mulvenna, M. D., et al., eds., Personalization on the Net Using Web Mining, A Collection of Articles, CACM, Vol. 43, No. 8, 2000.

Ng, R. T., L. V. S. Lakshmanan, J. Han, A. Pang, Exploratory Mining and Optimization of Constrained Association Queries, Technical Report, University of British Columbia and Concordia University, October 1997.

Park, J. S., M. Chen, P. S. Yu, Efficient Parallel Data Mining for Association Rules, Proceedings of the CIKM’95 Conference, Baltimore, MD, 1995, pp. 31–36.

Pinto, H., J. Han, J. Pei, K. Wang, Q. Chen, U. Dayal, Multi-Dimensional Sequential Pattern Mining, Proc. 2001 Int. Conf. on Information and Knowledge Management (CIKM’01), Atlanta, GA, November 2001.

Salzberg, S. L., Gene Discovery in DNA Sequences, IEEE Intelligent Systems, November/December 1999, pp. 44–48.

Spiliopoulou, M., The Laborious