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A soft-computing-based method for the automatic discovery of fuzzy rules in databases: Uses for academic research and management support in marketing

  • Albert Orriols-Puig*
  • , Francisco J. Martínez-López
  • , Jorge Casillas
  • , Nick Lee
  • *Corresponding author for this work

    Research output: Indexed journal article Articlepeer-review

    13 Citations (Scopus)

    Abstract

    The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method.

    Original languageEnglish
    Pages (from-to)1332-1337
    Number of pages6
    JournalJournal of Business Research
    Volume66
    Issue number9
    DOIs
    Publication statusPublished - Sept 2013

    Keywords

    • Fuzzy rules
    • KDD
    • Marketing decision support
    • Modeling
    • Unsupervised learning

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