图 书 馆
信息系谱：揭示非超链接文档数据库中的思想流Information Genealogy: Uncovering the Flow of Ideas in Non-Hyperlinked Document Databases |
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| 课程网址: | http://videolectures.net/kdd07_shaparenko_ig/ |
| 主讲教师: | Benyah Shaparenko |
| 开课单位: | 康奈尔大学 |
| 开课时间: | 2007-08-13 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We now have incrementally-grown databases of text documents ranging back for over a decade in areas ranging from personal email, to news-articles and conference proceedings. While accessing individual documents is easy, methods for overviewing and understanding these collections as a whole are lacking in number and in scope. In this paper, we address one such global analysis task, namely the problem of automatically uncovering how ideas spread through the collection over time. We refer to this problem as Information Genealogy. In contrast to bibliometric methods that are limited to collections with explicit citation structure, we investigate content-based methods requiring only the text and timestamps of the documents. In particular, we propose a language-modeling approach and a likelihood ratio test to detect influence between documents in a statistically well-founded way. Furthermore, we show how this method can be used to infer citation graphs and to identify the most influential documents in the collection. Experiments on the NIPS conference proceedings and the Physics ArXiv show that our method is more effective than methods based on document similarity. |
| 关 键 词: | 文本文档数据库; 语言建模; 似然比检验 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-05-09：lxf |
| 阅读次数: | 41 |