图 书 馆
识别文档集合中的时间模式和关键人物Identifying Temporal Patterns and Key Players in Document Collections |
|
| 课程网址: | http://videolectures.net/mlss06tw_shaparenko_itpkp/ |
| 主讲教师: | Benyah Shaparenko |
| 开课单位: | 康奈尔大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider the problem of analyzing the development of a document collection over time without requiring meaningful citation data. Given a collection of timestamped documents, we formulate and explore the following two questions. First, what are the main topics and how do these topics develop over time? Second, to gain insight into the dynamics driving this development, what are the documents and who are the authors that are most influential in this process? Unlike prior work in citation analysis, we propose methods addressing these questions without requiring the availability of citation data. The methods use only the text of the documents as input. Consequentially, they are applicable to a much wider range of document collections (email, blogs, etc.), most of which lack meaningful citation data. We evaluate our methods on the proceedings of the Neural Information Processing Systems (NIPS) conference. Even with the preliminary methods that we implemented, the results show that the methods are effective and that addressing the questions based on the text alone is feasible. In fact, the text-based methods sometimes even identify influential papers that are missed by citation analysis. |
| 关 键 词: | 文档集开发; 数据引用; 神经信息处理系统 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-16：cjy |
| 阅读次数: | 32 |