An Intelligent Transaction Assistant System for Electronic Commerce to Recommend Personalized Transaction Behavior

Abstract

Personalizedservice and friendly transaction environment are important factors in successful electronic commerce. This work proposes an intelligent interface to help customer transactions in electronic commerce. The system collects consuming behaviors by monitoring customer operations and recognizing the behavior patterns using RBF neural networks. The system then uses fuzzy c-means and grey theory to recommend personalized transaction behaviors for the customer.