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Top-10 Data Mining Case Studies

Author

Listed:
  • GABOR MELLI

    (PredictionWorks Inc., Seattle, WA 98126, USA)

  • XINDONG WU

    (Department of Computer Science, University of Vermont, Burlington, VT 05405, USA)

  • PAUL BEINAT

    (NeuronWorks International, Hurtsville, NSW 2220, Australia)

  • FRANCESCO BONCHI

    (Yahoo! Research, Barcelona, Spain)

  • LONGBING CAO

    (University of Technology, Sydney, Australia)

  • RONG DUAN

    (AT&T Labs, Research, Florham Park, NJ, USA)

  • CHRISTOS FALOUTSOS

    (Department of Computing Science, Carnegie Mellon University, 5000 Forber Avenue, Pittsburgh, PA 15213, USA)

  • RAYID GHANI

    (Accenture Technology Labs, 161 N.Clark St, Chicago, IL 60601, USA)

  • BRENDAN KITTS

    (Lucid Commerce, Seattle, WA 98104, USA)

  • BART GOETHALS

    (Department of Mathematics and Computer Science, University of Antwerp, Belgium)

  • GEOFF MCLACHLAN

    (Department of Mathematics, University of Queensland, St. Lucia, Brisbane, Australia)

  • JIAN PEI

    (School of Computing Science, Simon Fraser University, Canada)

  • ASHOK SRIVASTAVA

    (NASA, USA)

  • OSMAR ZAÏANE

    (Department of Computing Science, University of Alberta, Alberta, Canada T6G 2E8, Canada)

Abstract

We report on the panel discussion held at the ICDM'10 conference on the top 10 data mining case studies in order to provide a snapshot of where and how data mining techniques have made significant real-world impact. The tasks covered by 10 case studies range from the detection of anomalies such as cancer, fraud, and system failures to the optimization of organizational operations, and include the automated extraction of information from unstructured sources. From the 10 cases we find that supervised methods prevail while unsupervised techniques play a supporting role. Further, significant domain knowledge is generally required to achieve a completed solution. Finally, we find that successful applications are more commonly associated with continual improvement rather than by single "aha moments" of knowledge ("nugget") discovery.

Suggested Citation

  • Gabor Melli & Xindong Wu & Paul Beinat & Francesco Bonchi & Longbing Cao & Rong Duan & Christos Faloutsos & Rayid Ghani & Brendan Kitts & Bart Goethals & Geoff Mclachlan & Jian Pei & Ashok Srivastava , 2012. "Top-10 Data Mining Case Studies," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 389-400.
    • Handle: RePEc:wsi:ijitdm:v:11:y:2012:i:02:n:s021962201240007x
    DOI: 10.1142/S021962201240007X
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    Citations

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    Cited by:

    1. Robin Gubela & Artem Bequé & Stefan Lessmann & Fabian Gebert, 2019. "Conversion Uplift in E-Commerce: A Systematic Benchmark of Modeling Strategies," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 747-791, May.
    2. Gubela, Robin & Bequé, Artem & Gebert, Fabian & Lessmann, Stefan, 2018. "Conversion uplift in e-commerce: A systematic benchmark of modeling strategies," IRTG 1792 Discussion Papers 2018-062, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Si He & Nabil Belacel & Alan Chan & Habib Hamam & Yassine Bouslimani, 2016. "A Hybrid Artificial Fish Swarm Simulated Annealing Optimization Algorithm for Automatic Identification of Clusters," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 949-974, September.

    More about this item

    Keywords

    Data mining; cost-benefit analysis; case study; 68T05; 68U30; 68-01;
    All these keywords.

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