标题:
基于语义分析的微博推荐系统Weibo Recommendation System Based on Semantic Analysis
作者:
翟梦迪, 吴思霈, 刘雁娟
关键字:
微博词典, 分词, 特征词, 关联规则, 推荐系统, 微博Dictionary of Weibo, Cut Words, Key Words, Association Rules, Recommendation System, Weibo
期刊名称:
《Computer Science and Application》, Vol.6 No.9, 2016-09-22
摘要:
本文基于语义分析对博文内容进行主题提取，为使主题词更加准确构造的微博词典，通过分词、关键词提取对文本进行预处理，进而构建基于关联规则的微博推荐系统，为用户所感兴趣的内容进行精准推荐。
In this paper, we get Weibo’s theme by semantic analysis. In order to make the subject more accu-racy, we create the dictionary of Weibo. Then, we use the method of word segmentation, keyword extraction to analysis the text in advance, and we build Weibo recommendation system based on association rules, recommend the theme that users are interested in more accurately.