图 书 馆
用于信息抽取的耦合半监督学习Coupled Semi-Supervised Learning for Information Extraction |
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| 课程网址: | http://videolectures.net/wsdm2010_carlson_cssl/ |
| 主讲教师: | Andrew Carlson |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2010-03-18 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider the problem of semi-supervised learning to extract categories (e.g., academic fields, athletes) and relations (e.g., PlaysSport (athlete, sport)) from web pages, starting with a handful of labeled training examples of each category or relation, plus hundreds of millions of unlabeled web documents. Semi-supervised training using only a few labeled examples is typically unreliable because the learning task is underconstrained. This paper pursues the thesis that much greater accuracy can be achieved by further constraining the learning task, by coupling the semi-supervised training of many extractors for different categories and relations. We characterize several ways in which the training of category and relation extractors can be coupled, and present experimental results demonstrating significantly improved accuracy as a result. |
| 关 键 词: | 半监督学习; 标记样本; 学术领域 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-09-24：dingaq |
| 阅读次数: | 83 |