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Contribution to Book
Direct marketing modeling using evolutionary Bayesian network learning algorithm
Marketing intelligent systems using soft computing : managerial and research applications
  • Man Leung WONG, Lingnan University, Hong Kong
Document Type
Book chapter
Publication Date
1-1-2010
Publisher
Springer
Keywords
  • Direct Marketing Modeling,
  • Data Mining,
  • Bayesian Networks,
  • Evolutionary Algorithms
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.
DOI
10.1007/978-3-642-15606-9_18
Publisher Statement

Copyright © Springer-Verlag Berlin Heidelberg 2010

Access to external full text or publisher's version may require subscription.

Additional Information
ISBN of the source publication: 9783642156052
Full-text Version
Publisher’s Version
Citation Information
Wong, M. L. (2010). Direct marketing modeling using evolutionary Bayesian network learning algorithm. In J. Casillas & F. J. Martínez-López (Eds.), Marketing intelligent systems using soft computing: Managerial and research applications (pp.273-294). doi: 10.1007/978-3-642-15606-9_18