计算机工程与应用2016，Vol.52Issue(6)：50-54,5.DOI:10.3778/j.issn.1002-8331.1405-0179
基于LDA和CTR的用户模型分析
Analysis of user model based on LDA and CTR
摘要
Abstract
Personal service is a hot topic. But how to construct an integrated user model remains a challenge for us. This paper makes use of the topic model LDA to infer the user model. In order to improve precision, CTR is put into use for restrict of feature vector. With a few manual factors, the machine generates a training topic model. Based on this model, 100 users’micro-log messages regarded as test data will be applied for evaluating the quality of recommendation. The results show that the recommendation of celebrity performs better than the recommendation of news. Generally speaking, personal service is satisfying.关键词
隐形狄雷克雷分布(LDA)/主题模型/基于主题模型的协同过滤(CTR)/用户模型/推荐Key words
Latent Dirichlet Allocation(LDA)/topic model/Collaborative Topic Regression(CTR)/user model/recom-mendation分类
信息技术与安全科学引用本文复制引用
吴飞飞,姬东鸿,吕超镇..基于LDA和CTR的用户模型分析[J].计算机工程与应用,2016,52(6):50-54,5.基金项目
国家自然科学基金重点项目（No.61133012）；国家自然科学基金面上项目（No.61173062）。 （）
