This publication is the fruit of a collaborative research between academics from the marketing and the artificial intelligence fields. It presents a brand new methodology to be applied in marketing (causal) modeling. Specifically, we apply it to a consumer behavior model used for the experimentation. The characteristics of the problem (with uncertain data and available knowledge from a marketing expert) and the multiobjective optimization we propose make genetic fuzzy systems a good tool for tackling it. In sum, by applying this methodology we obtain useful information patterns (fuzzy rules) which help to better understand the relations among the elements of the marketing system (causal model) being analyzed; in our case, a consumer model.
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Casillas, J., Martínez-López, F.J. (2008). KDD in Marketing with Genetic Fuzzy Systems. In: Maimon, O., Rokach, L. (eds) Soft Computing for Knowledge Discovery and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-69935-6_10
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DOI: https://doi.org/10.1007/978-0-387-69935-6_10
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