Web Service下的商品推荐系统的研究与实现

Smart Recommendation: Research and Implement of the Product Recommendation System on E-commerce

基于电子商务平台的Webservice已经是广大消费者购买或者浏览商品的主要形式之一.但是,网络上的海量信息也给我们带来了很多不便.对于用户来说,如何及时地发现所需要的商品已经变得越来越困难.本文综合运用了关联挖掘、智能推荐算法等机器学习方法提出了一个WebService下的产品智能推荐Agent模型:SmartRecommendation,该系统通过对用户的历史交易记录的分析,挖掘出客户的购买模式和购买兴趣,并根据发现的模式对用户进行商品的智能推荐.实验结果表明,推荐模型具有较高的准确性,并且对用户的购买行为有一定的指导作用.

Web service on Electronic commerce has been one of the major forms of purchase or browse by a large number of consumer. However, magnanimity information on web brings us much inconvenience. How to find what one need has become more and more difficult to users. In this article, We integrate some machine learning method such as association mine and intelligent recommendation arithmetic to bring forward a product intelligent recommendation model——Agent:Smart Recommendation,this system mine purchase model and interest of users by analyzing their historic trade record, in turn ,by which it process the product recommendation to consumers. The results of the experiment show that the proposed method has higher precision on the product recommendation and have some guidance to the users' behaviors.