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 language | English |
|---|---|
| Pages (from-to) | 1332-1337 |
| Number of pages | 6 |
| Journal | Journal of Business Research |
| Volume | 66 |
| Issue number | 9 |
| Early online date | 12 Jul 2012 |
| DOIs | |
| Publication status | Published - Sept 2013 |
Keywords
- fuzzy rules
- KDD
- marketing decision support
- modeling
- unsupervised learning
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