An Adaptive Interface for Customer Transaction Assistant in Electronic Commerce

Personalized service and adaptive interface play important factors in electronic commerce. This work proposes an adaptive interface to for helping the customer transaction in electronic commerce. The adaptive interface collects the consumer behaviors by monitoring the customer operations, excluding unnecessary operations, and recognizing the behavior patterns. The interface uses the Bayesian belief network and the RBF neural networks to achieve the above tasks. The interface then evaluates knowledge and skill proficiency according to the customer behavior patterns. Finally, the interface generates the adaptive interface to the consumers for helping the transaction process