图 书 馆
主题链接LDA：主题和作者社区的联合模型Topic-Link LDA: Joint Models of Topic and Author Community |
|
| 课程网址: | http://videolectures.net/icml09_liu_tllda/ |
| 主讲教师: | Yan Liu |
| 开课单位: | 南加利福尼亚大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Given a large-scale linked document collection, such as a collection of blog posts or a research literature archive, there are two fundamental problems that have generated a lot of interest in the research community. One is to identify a set of high-level topics covered by the documents in the collection; the other is to uncover and analyze the social network of the authors of the documents. So far these problems have been viewed as separate problems and considered independently from each other. In this paper we argue that these two problems are in fact inter-dependent and should be addressed together. We develop a Bayesian hierarchical approach that performs topic modeling and author community discovery in one unified framework. The effectiveness of our model is demonstrated on two blog data sets in different domains and one research paper citation data from CiteSeer. |
| 关 键 词: | 贝叶斯分层方法; 博客数据集; 文档集合 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-23：lxf |
| 阅读次数: | 43 |