A Utility-based Recommendation Approach for E-Commerce Websites Based on Bayesian Networks
Although utility-based recommendation in E-Commerce can provide much better recommendation accuracy, there are still no effective approaches to build the utility function of each user. In order to overcome this problem, an approach based on Bayesian networks is proposed. Firstly, based on the common user utility function of a specific commodity which has already been constructed by domain experts, a prior Bayesian network can be established. Secondly, the prior Bayesian network is modified based on the current users implicit feedback, so that his utility function can be represented by means of Bayesian networks. Finally, according to his utility function, objects the current user may like are recommended to him. Compared with other approaches, this approach may acquire utility functions more approximately and automatically. Furthermore, it could extend the range of applications for which utility-based recommendation would be more useful.
E-Commerce utility-based recommendation Bayesian networks
Ming Yi Weihua Deng
Department of Information Management Huazhong Normal University Wuhan, 430079, China School of Economy & Management Huazhong Agriculture University Wuhan, 430070, China
国际会议
北京
英文
571-574
2009-07-24（万方平台首次上网日期，不代表论文的发表时间）