Collaborative Filtering Recommendation Model Based on User’s Credibility Clustering

摘要：

　　Aiming at the long response time,inaccurate recommendation and cold-start problems that faced by present recommendation algorithm,this paper,taking movie recommendation system as an example,proposes a collaborative filtering recommendation model based on user’s credibility clustering.This model divides recommendation process into offline and online phases.Offline,it uses the result of user’s credibility for clustering and then writes the clustered information into a table in database.Online,finds the cluster that target user belongs to and then gives recommendation.As a whole,the model reduces the response time,improves the accuracy of the recommendation rate,and solves the new user’s cold-start problem.

关键词： Collaborative Filtering Users Credibility Dynamic Clustering

作者: Zhao Xu Qiao Fuqiang

作者单位: Tianjin Sino-German Vocational Technical College Tianjin,China

会议类型: 国际会议

会议名称: The 13th International Symposium on Distributed Computing and Applications to Business,Engineering and Science(DCABES 2014)(第十三届分布式计算及其应用国际学术研讨会)

会议地点: 湖北咸宁

会议语种:英文

页码: 234-238

在线出版日期: 2014-11-24（万方平台首次上网日期，不代表论文的发表时间）