Business Intelligence for Strategic Marketing: Predictive Modelling of Customer Behaviour Using Fuzzy Logic and Evolutionary Algorithms

Authors:
Andrea G. Tettamanzi;Maria Carlesi;Lucia Pannese;Mauro Santalmasi
Affiliations:
Università degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione, via Bramante 65, I-26013 Crema, Italy;imaginary s.r.l., c/o Acceleratore d'Impresa del Politecnico di Milano, Via Garofalo 39, I-20133 Milan, Italy;imaginary s.r.l., c/o Acceleratore d'Impresa del Politecnico di Milano, Via Garofalo 39, I-20133 Milan, Italy;imaginary s.r.l., c/o Acceleratore d'Impresa del Politecnico di Milano, Via Garofalo 39, I-20133 Milan, Italy
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

Citing 4
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Abstract

This paper describes an application of evolutionary algorithms to the predictive modelling of customer behaviour in a business environment. Predictive models are represented as fuzzy rule bases, which allows for intuitive human interpretability of the results obtained, while providing satisfactory accuracy. An empirical case study is presented to show the effectiveness of the approach.