Name
Abstract | ||
|---|---|---|
Detection of fake news has spurred widespread interests in areas such as healthcare and Internet societies, in order to prevent propagating misleading information for commercial and political purposes. However, efforts to study a general framework for exploiting knowledge, for judging the trustworthiness of given news based on their content, have been limited. Indeed, the existing works rarely consider incorporating knowledge graphs (KGs), which could provide rich structured knowledge for better language understanding. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.websem.2021.100646 | Journal of Web Semantics |
Keywords | DocType | Volume |
Knowledge graph,Knowledge graph embedding,Multi-channel,Deep learning,Fake news detection | Journal | 70 |
ISSN | Citations | PageRank |
1570-8268 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinshuo Liu | 1 | 6 | 1.81 |
| Chenyang Wang | 2 | 0 | 0.34 |
| Chenxi Li | 3 | 25 | 11.27 |
| Ningxi Li | 4 | 6 | 0.80 |
| Juan Deng | 5 | 1 | 1.04 |
| Jeff Z. Pan | 6 | 16 | 4.13 |