Customer online shopping behaviours analysis using Bayesian networks

Publication Type:
Conference Proceeding
AI 2006: Advances in artificial intelligence, 2006, pp. 1293 - 1297
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This study applies Bayesian network technique to analyse the relationships among customer online shopping behaviours and customer requirements. This study first proposes an initial behaviour-requirement relationship model as domain knowledge. Through conducting a survey customer data is collected as evidences for inference of the relationships among the factors described in the model. After creating a graphical structure, this study calculates conditional probability distribution among these factors, and then conducts inference by using the Junction-tree algorithm. A set of useful findings has been obtained for customer online shopping behaviours and their requirements with motivations. These findings have potential to help businesses adopting more suitable online system development.
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