Data Mining Mehmed Kantardzic (good english books to read .txt) 📖

today. We expect that new generations of data-mining tools and methodologies will increase and extend the spectrum of application domains.

Note

1 A gigajoule (GJ) is a metric term used for measuring energy use. For example, 1 GJ is equivalent to the amount of energy available from either: 277.8 kWh of electricity, or 26.1 m3 of natural gas, or 25.8 L of heating oil.

BIBLIOGRAPHY

CHAPTER 1

Adriaans, P., D. Zantinge, Data Mining, Addison-Wesley Publ. Co., New York, 1996.

Agosta, L., The Essential Guide to Data Warehousing, Prentice Hall, Inc., Upper Saddle River, NJ, 2000.

An, A., C. Chun, N. Shan, N. Cercone, W. Ziarko, Applying Knowledge Discovery to Predict Watter-Supply Consumption, IEEE Expert, July/August 1997, pp. 72–78.

Barquin, R., H. Edelstein, Building, Using, and Managing the Data Warehouse, Prentice Hall, Inc., Upper Saddle River, NJ, 1997.

Ben, H., E. King, How to Prepare for Data Mining, http://www.b-eye-network.com/channels/1415/view/10880, July 2009.

Berson, A., S. Smith, K. Thearling, Building Data Mining Applications for CRM, McGraw-Hill, New York, 2000.

Bischoff, J., T. Alexander, Data Warehouse: Practical Advice from the Experts, Prentice Hall, Inc., Upper Saddle River, NJ, 1997.

Brachman, R. J., T. Khabaza, W. Kloesgen, G. S. Shapiro, E. Simoudis, Mining Business Databases, CACM, Vol. 39, No. 11, 1996, pp. 42–48.

De Ville, B., Managing the Data Mining Project, Microsoft Data Mining, 2001, pp. 93–116.

Djoko, S., D. J. Cook, L. B. Holder, An Empirical Study of Domain Knowledge and Its Benefits to Substructure Discovery, IEEE Transactions on Knowledge and Data Engineering, Vol. 9, No. 4, 1997, pp. 575–585.

Fayyad, U., G. P. Shapiro, P. Smyth, The KDD Process for Extracting Useful Knowledge from Volumes of Data, CACM, Vol. 39, No. 11, 1966, pp. 27–34.

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

Fayyad, U., G. P. Shapiro, P. Smyth, From Data Mining to Knowledge Discovery in Databases, AI Magazine, Fall 1996b, pp. 37–53.

Friedland, L., Accessing the Data Warehouse: Designing Tools to Facilitate Business Understanding, Interactions, January–February 1998, pp. 25–36.

Ganti, V., J. Gehrke, R. Ramakrishnan, Mining Very Large Databases, Computer, Vol. 32, No. 8, 1999, pp. 38–45.

Groth, R., Data Mining: A Hands-On Approach for Business Professionals, Prentice Hall, Inc., Upper Saddle River, NJ, 1998.

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

Kaudel, A., M. Last, H. Bunke, eds., Data Mining and Computational Intelligence, Physica-Verlag, Heidelberg, Germany, 2001.

Kriegel, H. P., et al., Future Trends in Data Mining, Data Mining and Knowledge Discovery, Vol. 15, 2007, pp. 87–97.

Lavrac, N., et al., Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving, Machine Learning, Vol. 57, 2004, pp. 13–34.

Maxus Systems International, What Is Data Mining, Internal Documentation, http://www.maxussystems.com/datamining.html.

Olson, D. L., Data mining in business services, Service Business, Springer Berlin/Heidelberg, Vol. 1, No. 3, 2007, pp. 181–193.

Pyle, D., Getting the Initial Model: Basic Practices of Data Mining, Business Modeling and Data Mining, 2003, pp. 361–425.

Ramakrishnan, N., A. Y. Grama, Data Mining: From Serendipity to Science, Computer, Vol. 32, No. 8, 1999, pp. 34–37.

Shapiro, G. P., The Data-Mining Industry Coming of Age, IEEE Intelligent Systems, November/December 1999, pp. 32–33.

Thomsen, E., OLAP Solution: Building Multidimensional Information System, John Wiley, New York, 1997.

Thuraisingham, B., Data Mining: Technologies, Techniques, Tools, and Trends, CRC Press LLC, Boca Raton, FL, 1999.

Tsur, S., Data Mining in the Bioinformatics Domain, Proceedings of the 26th YLDB Conference, Cairo, Egypt, 2000, pp. 711–714.

Two Crows Corp., Introduction to Data Mining and Knowledge Discovery, Two Crows Corporation, Maryland, 2005.

Waltz, D., S. J. Hong, Data Mining: A Long Term Dream, IEEE Intelligent Systems, November/December 1999, pp. 30–34.

CHAPTER 2

Adriaans, P., D. Zantinge, Data Mining, Addison-Wesley Publ. Co., New York, 1996.

Anand, S. S., D. A. Bell, J. G. Hughes, The Role of Domain Knowledge in Data Mining, Proceedings of the CIKM’95 Conference, Baltimore, 1995, pp. 37–43.

Barquin, R., H. Edelstein, Building, Using, and Managing the Data Warehouse, Prentice Hall, Inc., Upper Saddle River, NJ, 1997.

Ben, H., E. King, How to Prepare for Data Mining, http://www.b-eye-network.com/channels/1415/view/10880, July 2009.

Berson, A., S. Smith, K. Thearling, Building Data Mining Applications for CRM, McGraw-Hill, New York, 2000.

Bischoff, J., T. Alexander, Data Warehouse: Practical Advice from the Experts, Prentice Hall, Inc., Upper Saddle River, NJ, 1997.

Boriah, S., V. Chandola, V. Kumar, Similarity Measures for Categorical Data: A Comparative Evaluation, SIAM Conference, 2008, pp. 243–254.

Brachman, R. J., T. Khabaza, W. Kloesgen, G. S. Shapiro, E. Simoudis, Mining Business Databases, CACM, Vol. 39, No. 11, 1996, pp. 42–48.

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

Clark, W. A. V., M. C. Deurloo, Categorical Modeling/Automatic Interaction Detection, Encyclopedia of Social Measurement, 2005, pp. 251–258.

Dwinnell, W., Data Cleansing: An Automated Approach, PC AI, March/April 2001, pp 21–23.

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

Fayyad, U., D. Haussier, P. Stolorz, Mining Scientific Data, CACM, Vol. 39, No. 11, 1966b, pp. 51–57.

Ganti, V., J. Gehrke, R. Ramakrishnan, Mining Very Large Databases, Computer, Vol. 32, No. 8, 1999, pp. 38–45.

Groth, R., Data Mining: A Hands-On Approach for Business Professionals, Prentice hall, Inc., Upper Saddle River, NJ, 1998.

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

Liu, H., H. Motoda, eds., Feature Extraction, Construction and Selection: A Data Mining Perspective, Kluwer Academic Publishers, Boston, MA, 1998.

Liu, H., H. Motoda, Feature Selection for Knowledge Discovery and Data Mining, Second Printing, Kluwer Academic Publishers, Boston, 2000.

Pass, S., Discovering Value in a Mountain of Data, OR/MS Today, October 1997, 24–28.

Pyle, D., Data Preparation for Data Mining, Morgan Kaufmann Publ. Inc., New York, 1999.

Refaat, M., Treatment of Missing Values, Data Preparation for Data Mining Using SAS, 2007, pp. 171–206.

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

Weiss, S. M., N. Indurkhya, Predictive Data Mining: A Practical Guide, Morgan Kaufman Publishers, Inc., San Francisco, 1998.

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