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Data Mining as Support to Knowledge Management in Marketing

Author

Listed:
  • Zekić-Sušac Marijana
  • Has Adela

    (Faculty of Economics in Osijek, Croatia)

Abstract

Background: Previous research has shown success of data mining methods in marketing. However, their integration in a knowledge management system is still not investigated enough.

Suggested Citation

  • Zekić-Sušac Marijana & Has Adela, 2015. "Data Mining as Support to Knowledge Management in Marketing," Business Systems Research, Sciendo, vol. 6(2), pages 18-30, September.
    • Handle: RePEc:bit:bsrysr:v:6:y:2015:i:2:p:18-30
    DOI: 10.1515/bsrj-2015-0008
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    Citations

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    Cited by:

    1. Kenda Klemen & Mladenić Dunja, 2018. "Autonomous Sensor Data Cleaning in Stream Mining Setting," Business Systems Research, Sciendo, vol. 9(2), pages 69-79, July.
    2. Mirjana Pejić Bach & Živko Krstić & Sanja Seljan & Lejla Turulja, 2019. "Text Mining for Big Data Analysis in Financial Sector: A Literature Review," Sustainability, MDPI, vol. 11(5), pages 1-27, February.
    3. Opiła Janusz, 2019. "Role of Visualization in a Knowledge Transfer Process," Business Systems Research, Sciendo, vol. 10(1), pages 164-179, April.
    4. Aleksandar Grubor & Olja Jaksa, 2018. "Internet Marketing as a Business Necessity," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 16(2), pages 265-274.

    More about this item

    Keywords

    association rules; data mining; knowledge management; marketing; neural networks; C4; C45;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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