TOPIC-VECTOR BASED USER MODEL FOR SOCIAL TAGGING SYSTEMS

摘要：

According to the effect of enriching semantic information, social tagging systems have been regarded as novel information source for modeling user in personalized recommendation.Till now, most researchers construct the user model using weighted tag-vector.Although the simple and intuitively reasonable it is, the weighted tag-vector model has drawbacks including data sparsity problem and semantic ambiguity problem.In this paper, a topicvector based user model is presented to solve the data sparsity problem and semantic ambiguity problem. With the discussion of the presented experiment, the validity of the modeling method was verified.

关键词： social tagging user modeling personalized recommendation data sparsity semantic ambiguity

作者: YINGHAO HE SHIMIN SHAN WENLI LI FAN ZHANG

作者单位: School of Management,Dalian University of technology,Liaoning Province,Dalian,China City Institute,D School of Software,Dalian University of technology,Liaoning Province,Dalian,China School of Management,Dalian University of technology,Liaoning Province,Dalian,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 1328-1333

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）