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Data mining in business services

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  • David L. Olson

Abstract

Data mining applies traditional statistical tools as well as artificial intelligence algorithms to the analysis of large datasets. Data mining has proven very effective in many fields, including business. This paper reviews applications of data mining relevant to the service industry, and demonstrates primary business functions and data mining methods. Typical industry data mining process is described, analytic tools are reviewed, and major software tools noted. Copyright Springer-Verlag 2007

Suggested Citation

  • David L. Olson, 2007. "Data mining in business services," Service Business, Springer;Pan-Pacific Business Association, vol. 1(3), pages 181-193, September.
  • Handle: RePEc:spr:svcbiz:v:1:y:2007:i:3:p:181-193
    DOI: 10.1007/s11628-006-0014-7
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    References listed on IDEAS

    as
    1. K A Smith & R J Willis & M Brooks, 2000. "An analysis of customer retention and insurance claim patterns using data mining: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(5), pages 532-541, May.
    2. N M Adams & D J Hand & R J Till, 2001. "Mining for classes and patterns in behavioural data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(9), pages 1017-1024, September.
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    Cited by:

    1. Gitae Kim & Bongsug Chae & David Olson, 2013. "A support vector machine (SVM) approach to imbalanced datasets of customer responses: comparison with other customer response models," Service Business, Springer;Pan-Pacific Business Association, vol. 7(1), pages 167-182, March.
    2. Dinah Payne & Brett J. L. Landry, 2012. "A Composite Strategy for the Legal and Ethical Use of Data Mining," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 1(1), pages 27-43.
    3. Yen-Chun Chou & Howard Hao-Chun Chuang, 2018. "A predictive investigation of first-time customer retention in online reservation services," Service Business, Springer;Pan-Pacific Business Association, vol. 12(4), pages 685-699, December.

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