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 Cassilas, Nicholas Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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. © 2012 Published by Elsevier Inc.

Original languageEnglish
Pages (from-to)1332-1337
Number of pages6
JournalJournal of Business Research
Volume66
Issue number9
Early online date12 Jul 2012
DOIs
Publication statusPublished - Sep 2013

Keywords

  • fuzzy rules
  • KDD
  • marketing decision support
  • modeling
  • unsupervised learning

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