Recommendation based on bipartite network of two-step model

摘要：

　　Traditional recommendation only uses the single model of selection or rating to mining the users interests.Network-Based Inference (NBI) is typical of selection single model.In order to make full use of information, in this paper, Recommendation based on bipartite network of two-step model(RBNTM) is put forward.The method on the basis of Network-based inference, considering scores also reflects the degree of the user preferences, combining NBI and rating prediction with two-step model to improve the accuracy of the prediction.On MoiveLens datasets experiments show that the proposed, RBNTM is effective.

关键词： two-step model bipartite network recommendation

作者: Liting Wei Yun Li

作者单位: College of Information Engineering Yangzhou University Yangzhou, China

会议类型: 国际会议

会议名称: The 13th Web Information Systems and Applications Conference(第十三届全国web信息系统及其应用学术会议)(WISA2016)、The 1st Symposium on Big Data Processing and Analysis)( BDPA 2016)第一届全国大数据处理与分析学术研讨会、The 1st Workshop on Information System Security)(ISS2016)(第一届全国信息系统安全研讨会

会议地点: 武汉

会议语种:英文

页码: 56-60

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）