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Data mining

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References

  1. Bradley, P., Fayyad, U., and Mangasarian, O. (1999). “Mathematical Programming for Data Mining: Formulations and Challenges,” INFORMS Jl. Computing, 11.

    Google Scholar 

  2. Chester, T. (1999). “Sizes of some large databases,” Fallbrook, California (also available via http://sd.znet.com/~schester/facts/databases_sizes.html/).

    Google Scholar 

  3. Data Mining News (1998). Vol. 1, No. 17.

    Google Scholar 

  4. Data Mining News (1998). Vol. 1, No. 22.

    Google Scholar 

  5. Data Mining News (1999). Vol. 2, No. 10.

    Google Scholar 

  6. Hayes, H. (1999). “The New and Improved Tax Collector,” CNN Interactive, April 7.

    Google Scholar 

  7. Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. (1996). “From Data Mining to Knowledge Discovery in Databases,” AI Magazine, Fall.

    Google Scholar 

  8. Fayyad, U. and Bradley, P. (1998). “Tutorial on Data Mining and Knowledge Discovery in Databases, II,” at INFORMS Fall National Meeting, Seattle, Washington.

    Google Scholar 

  9. Garfinkel, S. (1998). “Threats to privacy: new science called datamining could benefit consumers–or harass them,” The Boston Globe, July 16.

    Google Scholar 

  10. Grossman, R., Kasif, S., Moore, R., Rocke, D., and Ullman, J. (1999). “Data Mining Research: Opportunities and Challenges,” a report of three Workshops on Mining Large, Massive and Distributed Data, National Science Foundation, Washington, DC.

    Google Scholar 

  11. Hoffman, T. (1998). “Banks Turn to IT to Reclaim Most Profitable Customers,” Computer World, December 7.

    Google Scholar 

  12. Hoffman, T. (1999). “Insurers Mine Age-Appropriate Offering,” Computer World, April 19.

    Google Scholar 

  13. IBM (1999). “Data Mining — An IBM Overview,” Boulder, Colorado (also available via http://direct.boulder.ibm.com/bi/info/overview/htm).

    Google Scholar 

  14. Mangasarian, O. (1965). “Linear and Nonlinear Separation of Patterns by Linear Programming,” Operations Research, 13, 444–452.

    Google Scholar 

  15. Thyfault, M. (1999). “Data Mining for Audio–Dragon Systems Uses Speech Recognition to Cull Data from Call-Center Tapes,” Information Week, February 8.

    Google Scholar 

  16. Two Crows Corp. (1999). “Introduction to Data Mining and Knowledge Discovery” (2nd ed.), Potomac, Maryland (also available via http://direct.boulder.ibm.com/bi/info/overview.htm).

    Google Scholar 

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Author information

Authors and Affiliations

  1. Oklahoma State University, Stillwater, USA

    Syam Menon & Ramesh Sharda

Authors
  1. Syam Menon
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  2. Ramesh Sharda
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Editor information

Editors and Affiliations

  1. Robert H. Smith School of Business, University of Maryland, College Part, Maryland, USA

    Saul I. Gass

  2. School of Information Technology & Engineering, George Mason University, Fairfax, Virginia, USA

    Carl M. Harris

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© 2001 Kluwer Academic Publishers

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Menon, S., Sharda, R. (2001). Data mining . In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_213

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  • DOI: https://doi.org/10.1007/1-4020-0611-X_213

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-7923-7827-3

  • Online ISBN: 978-1-4020-0611-1

  • eBook Packages: Springer Book Archive

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