【摘 要】 A challenge for current e-commerce systems is to improve customer satisfaction by providing instruments for the personalised offer of products. Personalised recommender systems are endowed with intelligent mechanisms to search products that users are... 更多 >> A challenge for current e-commerce systems is to improve customer satisfaction by providing instruments for the personalised offer of products. Personalised recommender systems are endowed with intelligent mechanisms to search products that users are interested in. In this paper, we integrate software engineering and web mining techniques in the development of an e-commerce recommender system capable of predicting the preferences of its users and present them a personalised catalogue. A data mining model induced by a decision tree algorithm is used to predict clients' preferences. The system also has an internationalisation automatic mechanism that facilitates the visualisation of the user's interface in different languages. << 收起
