图 书 馆
基于知识图的基于内容的假新闻检测Content based Fake News Detection Using Knowledge Graphs |
|
| 课程网址: | http://videolectures.net/iswc2018_pan_content_fake_news/ |
| 主讲教师: | Jeff Z. Pan |
| 开课单位: | 南安普顿大学 |
| 开课时间: | 2018-11-22 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This paper addresses the problem of fake news detection. Although there are many works already in this space, most of them are not using the content itself for the decision making. In this paper, we propose some novel approaches to detecting fake news by making use of knowledge graphs. There are a few technical challenges. Firstly, state of the art triple extraction tools are still far from perfect. Secondly, it is challenging to validate the correctness of the extracted triples. Thirdly, open knowledge graphs, such as DBPedia, are not comprehensive enough to cover all the relations needed for fake news detection. To address these challenges, we propose three approaches, which are evaluated with Kaggle's "Getting Real about Fake News" dataset. Our studies indicate some insights, despite the above mentioned challenges, on using knowledge graph for fake news detection. |
| 关 键 词: | 假新闻检测问题; 知识图检测假新闻; 假新闻检测所需关系; 开放知识图 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-01-06：cyh |
| 最后编审: | 2023-01-07：cyh |
| 阅读次数: | 57 |