Research on Improving the Real time of E-commerce Personalized Recommendation System

摘要：

In order to solve the problem that E-commerce personalized recommendation system cannot act in real-time on users access, page increasing or decreasing and site structure changing, this paper proposed a new model based on page clustering. The model consist with the offline and online parts, and used a directed weighted graph to represent the Web access model, then defined a new degree of user access interest, especially proposed three algorithm: the clustering algorithm, the updating clustering sets algorithm and the recommending algorithm. Finally, this paper verified the feasibility of the model by experiments with Visual Studio 2005 software. Experiment shows that the new model can solve the real-time problem of existing E-commerce personalized recommendation system effectively.

关键词： Recommended Model Page clustering Directed weighted graph Degree of user interest Web dynamic

作者: Li He YueHe

作者单位: Business SchoolSichuan UniversityChengdu, China Business SchoolSichuan University Chengdu, China

会议类型: 国际会议

会议名称: 2010 International Conference on Digital Enterprise and Digital Manufacturing(2010年数字化企业与数字化制造国际会议 DEDM 2010)

会议地点: 成都

会议语种:英文

页码: 61-64

在线出版日期: 2010-12-03（万方平台首次上网日期，不代表论文的发表时间）