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Marketing Intelligent Systems Using Soft Computing pp 273–294Cite as

Direct Marketing Modeling Using Evolutionary Bayesian Network Learning Algorithm

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 258))

Abstract

Direct marketing modeling identifies effective models for improving managerial decision making in marketing. This paper proposes a novel system for discovering models represented as Bayesian networks from incomplete databases in the presence of missing values. It combines an evolutionary algorithm with the traditional Expectation-Maximization(EM) algorithm to find better network structures in each iteration round. A data completing method is also presented for the convenience of learning and evaluating the candidate networks. The new system can overcome the problem of getting stuck in sub-optimal solutions which occurs in most existing learning algorithms and the efficiency problem in some existing evolutionary algorithms. We apply it to a real-world direct marketing modeling problem, and compare the performance of the discovered Bayesian networks with other models obtained by other methods. In the comparison, the Bayesian networks learned by our system outperform other models.

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Author information

Authors and Affiliations

  1. Department of Computing and Decision Sciences, Lingnan University, Tuen Mun, Hong Kong

    Man Leung Wong

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  1. Man Leung Wong
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Editor information

Editors and Affiliations

  1. University of Granada, Spain

    Jorge Casillas  & Francisco J. Martínez-López  & 

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Wong, M.L. (2010). Direct Marketing Modeling Using Evolutionary Bayesian Network Learning Algorithm. In: Casillas, J., Martínez-López, F.J. (eds) Marketing Intelligent Systems Using Soft Computing. Studies in Fuzziness and Soft Computing, vol 258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15606-9_18

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  • DOI: https://doi.org/10.1007/978-3-642-15606-9_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15605-2

  • Online ISBN: 978-3-642-15606-9

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