Research on Modeling Users Preference in the Steel E-trading Platform
In order to meet the increasing personalized needs of users in the steel trading platform,the intelligent recommendation system has been introduced into the platform.And the users interests and preferences-based modeling is the key and foundation of recommendation system,and changes with the change of time.So,in this paper,the user preferences are divided into long-term and short-term firstly,then the users basic information vectors and cluster method are used to model users long-term interests and preferences,while mining and analyzing users operating records in the platform to model users the short-term.Finally,the whole interest and preferences model of user will be built by integrating the two models.
Intelligent recommendation system users behavior long-term interest short-term interest
Ping Wu Tao Yu Jangbo Du Guoqing Qu Feng Xiong
Cims & Robot Center, Shanghai University, Shanghai, China
国际会议
重庆
英文
687-691
2015-03-02（万方平台首次上网日期，不代表论文的发表时间）