图 书 馆
通过语言建模识别文档的原始思想贡献Identifying the Original Contribution of a Document via Language Modeling |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_shaparenko_iocdlm/ |
| 主讲教师: | Benyah Shaparenko |
| 开课单位: | 康奈尔大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | One major goal of text mining is to provide automatic methods to help humans grasp the key ideas in ever-increasing text corpora. To this effect, we propose a statistically well-founded method for identifying the original ideas that a document contributes to a corpus, focusing on self-referential diachronic corpora such as research publications, blogs, email, and news articles. Our statistical model of passage impact defines (interesting) original content through a combination of impact and novelty, and the model is used to identify each document’s most original passages. Unlike heuristic approaches, the statistical model is extensible and open to analysis. We evaluate the approach both on synthetic data and on real data in the domains of research publications and news, showing that the passage impact model outperforms a heuristic baseline method. |
| 关 键 词: | 文本挖掘; 文本语料库; 统计模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-27：lxf |
| 阅读次数: | 45 |