图 书 馆
通过Dirichlet Forest Priors将领域知识纳入主题建模Incorporating Domain Knowledge into Topic Modeling via Dirichlet Forest Priors |
|
| 课程网址: | http://videolectures.net/icml09_andrzejewski_idk/ |
| 主讲教师: | David Andrzejewski |
| 开课单位: | 威斯康星大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Users of topic modeling methods often have knowledge about the composition of words that should have high or low probability in various topics. We incorporate such domain knowledge using a novel Dirichlet Forest prior in a Latent Dirichlet Allocation framework. The prior is a mixture of Dirichlet tree distributions with special structures. We present its construction, and inference via collapsed Gibbs sampling. Experiments on synthetic and real datasets demonstrate our model’s ability to follow and generalize beyond userspecified domain knowledge. |
| 关 键 词: | 吉布斯采样; 主题建模; 分配框架 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-07-14：yumf |
| 阅读次数: | 45 |