See also Introductory Books on Data Mining.

Data Mining Books: Professional and Business-oriented

• Jean-Marc Adamo, Data Mining For Association Rules and Sequential Patterns: Sequential and Parallel Algorithms, Springer Verlag, 2001.
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• Michael Berry & Gordon Linoff, Data Mining Techniques for Marketing, Sales and Customer Support, John Wiley & Sons, 1997.
• by Michael J. A. Berry, Gordon S. Linoff, Mining the Web: Transforming Customer Data, J. Wiley, 2002
• Alex Berson, Stephen J. Smith, Data Warehousing, Data Mining, and OLAP, McGraw Hill, 1997
• Alex Berson, Stephen Smith, and Kurt Thearling, Building Data Mining Applications for CRM, McGraw Hill
• M. Berthold, David J. Hand (Eds), Intelligent Data Analysis: An Introduction, Springer Verlag, ISBN 3540658084, 1999.
• Hamparsum Bozdogan (Editor), Statistical Data Mining and Knowledge Discovery, CRC Press, ISBN 1-58488-344-8, 2004.
• Dan Braha (Ed.), Data Mining for Design and Manufacturing: Methods and Applications, Kluwer, 2001
• M.A. Bramer (Ed.), Knowledge discovery and data mining: theory and practice, IEE Books, 1999
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• Peter Cabena, Pablo Hadjinian, Rolf Stadler, Jaap Verhees, Alessandro Zanasi, Discovering Data Mining from Concept to Implementation, Prentice Hall, 1997
• Patricia Cerrito, Introduction to Data Mining Using SAS Enterprise Miner, ISBN: 978-1-59047-829-5, SAS Press, 2006.
• S. Chakrabarti, Mining the Web: Discovering Knowledge from Hypertext Data, Morgan Kaufmann, ISBN 1-55860-754-4, 2002.
• Cios, K..J. (ed.), Medical Data Mining and Knowledge Discovery. Physica-Verlag (Springer), ISBN 3-7908-1340-0, 2000.
• Cios, K., W. Pedrycz, R. Swiniarski, Data Mining Methods for Knowledge Discovery, Kluwer, 1998, ISBN 0-7923-8252-8.
• Earl Cox, Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration, Morgan Kaufmann, ISBN 0-12-194275-9, 2004.
• C.L. Curotto & N.F.F. Ebecken, Implementing Data Mining Algorithms in Microsoft® SQL Server™, WIT Press, 2005.
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• Barry de Ville, Microsoft Data Mining, Integrated Business Intelligence for e-Commerce and Knowledge Management.
  ISBN 1555582427, 464pp, Paperback, February 2001
• Barry de Ville, Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner, SAS Press, ISBN 978-1-59047-567-6, Oct 2006.
• Rhonda Delmater, Monte Hancock, Data Mining Explained : A Manager's Guide to Customer-Centric Business Intelligence, Digital Press, ISBN 1555582311, 352 pages, January 2001.
• Vasant Dhar and Roger Stein, Seven Methods for Transforming Corporate Data Into Business Intelligence, Prentice Hall, 1996.
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• U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press, 1996 (order on-line from Amazon.com or from MIT Press).
• Usama Fayyad, Georges Grinstein, and Andreas Wierse, Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann, ISBN 1-55860-689-0, 2001.
• George Fernandez, Data Mining Using SAS Applications, CRC Press, 2003.
• Alex A. Freitas & Simon H. Lavington. Mining Very Large Databases with Parallel Processing. Kluwer, 1998. ISBN: 0-7923-8048-7
• Alex A. Freitas, Data Mining and Knowledge Discovery with Evolutionary Algorithms, Springer-Verlag, 2002. ISBN: 3-540-43331-7
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• Paolo Giudici, Applied Data Mining: Statistical Methods for Business and Industry, John Wiley, 376pp, 2003.
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• Joseph Y. Halpern, Reasoning About Uncertainty, MIT Press, 2003. ISBN 0-262-08320-5
• Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer Verlag, 2001.
• Mark F. Hornick, Erik Marcade, Sunil Venkayala, Java Data Mining: Strategy, Standard, and Practice - A Practical Guide for architecture, design, and implementation, Elsevier, 2006. ISBN 0123704529
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• A. Kandel, M. Last, and H. Bunke, Editors, Data Mining and Computational Intelligence, Physica-Verlag, Studies in Fuzziness and Soft Computing, Vol. 68, 2001. ISBN 3-7908-1371-0.
• Mehmed Kantardzic, Data Mining: Concepts, Models, Methods, and Algorithms, ISBN: 0471228524, Wiley-IEEE Press, 2002.
• Hillol Kargupta and Philip Chan, editors, Advances in Distributed and Parallel Knowledge Discovery, MIT/AAAI Press 2001, ISBN: 0262611554.
  This book presents introductions to Distributed KD and Parallel KD, extensive reviews of the field, and state-of-the-art techniques.
• Hillol Kargupta, Anupam Joshi, Krishnamoorthy Sivakumar and Yelena Yesh, editors, Data Mining: Next Generation Challenges and Future Directions, AAAI Press 2004, ISBN: 0-262-61203-8.
• Kennedy, Lee, Van Roy, Reed, and Lippman, Solving Data Mining Problems Through Pattern Recognition,
  Prentice Hall, ISBN: 0130950831, 1997.
• Willi Kloesgen and Jan Zytkow, eds, Handbook of Data Mining and Knowledge Discovery, Oxford University Press, Oct 2002.
• B. Kovalerchuk, E. Vityaev, Data Mining in Finance: Advances in Relational and Hybrid Methods, Kluwer, 2000, ISBN 0-7923-7804-0
• Stephan Kudyba and Richard Hoptroff, Data Mining AND Business Intelligence: A Guide to Productivity, IDEA-GROUP Publishing, 2001.
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• M. Last, A. Kandel, and H. Bunke (Editors), Data Mining in Time Series Databases, World Scientific, Series in Machine Perception and Artificial Intelligence, Vol. 57, 2004
• Gordon Linoff, Data Analysis using SQL and Excel, by John Wiley & Sons ISBN 0-470-09951-8, 2007.
• Huan Liu and Hiroshi Motoda, Feature Selection for Knowledge Discovery and Data Mining, Kluwer, 1998
• Huan Liu and Hiroshi Motoda, Feature Extraction, Construction and Selection: A Data Mining Perpective, Kluwer, 1998
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• O. Maimon and M. Last, Knowledge Discovery and Data Mining - The Info-Fuzzy Network (IFN) Methodology, Kluwer Publishers, Massive Computing, 2000. ISBN 0-7923-6647-6.
• Robert M. Mattison, Data Warehousing and Data Mining for Telecommunications, Artech House, 1997
• Randall Matignon, Data Mining Using SAS Enterprise Miner, v4.3.
• Ryszard S. Michalski, Ivan Bratko, Miroslav Kubat, eds., MACHINE LEARNING & DATA MINING: Methods and Applications, John Wiley, 1998.
• H. Miller, J. Han, editors, Geographic Data Mining and Knowledge Discovery, Research Monographs in Geographic Information Systems, Taylor and Francis, 2001.
• Boris Mirkin, Clustering for Data Mining: A Data Recovery Approach, CRC Press, 2005.
• Tom Mitchell, Machine Learning, McGraw Hill, 1997.
• Mitchie, Spiegelhalter, and Taylor, Machine Learning, Neural and Statistical Classification, (STATLOG project), 1994. Out of print, but freely available on the web.
• Masoud Mohammadian, Intelligent Agents for Data Mining and Information Retrieval, Idea Group Publishing, 2004, ISBN: 1-59140-194-1.
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• Hamid R. Nemati, Christopher D. Barko, Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance, Idea Group Publishing, 2003, ISBN 1-59140-134-8.
• Nong Ye (ed.), The Handbook of Data Mining. Taylor & Francis, 2003, ISBN 0-8058-4081-8. (689 pages).
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• Jack E. Olson, Data Quality: The Accuracy Dimension, Morgan Kaufmann, ISBN 1-55860-891-5, 2002
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• Perner, P. and Petrou, M. (Eds.), Machine Learning and Data Mining in Pattern Recognition, Springer Verlag, lnai 1715, Sept 1999
• Dorian Pyle, Data Preparation For Data Mining, Morgan Kaufmann, ISBN 1-55860-529-0, 1999
• Dorian Pyle, Business Modeling and Data Mining, Morgan Kaufmann, ISBN 155860653X, 2003.
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• Bruce Ratner, Statistical Modeling and Analysis for Database Marketers: Effective Techniques for Mining Big Data, Chapman & Hall/CRC Press, ISBN: 1-57444-344-5.
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• Shmueli, Galit, Nitin Patel, Peter Bruce, Data Mining for Business Intelligence, Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, ISBN: 0-470-08485-5, December 2006.
• Sommer, Friedrich T. and Andrzej Wichert (Eds.), Exploratory Analysis and Data Modeling in Functional Neuroimaging, MIT Press, 2002, 8 x 10, 352 pp., cloth, ISBN 0-262-19481-3.
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• by ZhaoHui Tang, Jamie MacLennan, Data Mining with SQL Server 2005, ISBN: 0471462616, Wiley, 2005.
• Bhavani Thuraisingham, Data Mining: Technologies, Techniques, Tools, and Trends, CRC Press, 1999
• Bhavani Thuraisingham, Managing and Mining Multimedia Databases, CRC Press, 1999
• M. Vazirgiannis, M. Halkidi, D. Gunopulos. Quality Assessment and Uncertainty Handling in Data Mining, Springer-Verlag, LNAI Series, July 2003.
• Chris Westphal, Teresa Blaxton, Data Mining Solutions, John Wiley, 1998