Please use this identifier to cite or link to this item:
https://elib.vku.udn.vn/handle/123456789/5825| Title: | Fake News Detection System, based on CBOW and BERT |
| Authors: | Vo, Trung Hung Imre, Felde Ninh, Khanh Chi |
| Keywords: | Fake News Detection CBOW BERT Transformer Natural Language Processing |
| Issue Date: | Jan-2025 |
| Publisher: | Acta Polytechnica Hungarica |
| Abstract: | Fake news is becoming a major challenge that greatly affects the public’s trust in the media. In this paper, we propose a new solution, combining word embedding based on CBOW (Continuous Bag Of Words) and the BERT (Bidirectional Encoder Representations from Transformers) models to support fake news detection. This paper focuses on presenting the proposed model and processing steps through the FND4Vn system, with a data set of Vietnamese news. Experimental results show that this solution achieves accuracy as high as 0.96 in recall and has many advantages compared to existing methods. |
| Description: | Acta Polytechnica Hungarica; Vol. 22, No. 1; pp: 27-41 |
| URI: | https://elib.vku.udn.vn/handle/123456789/5825 |
| ISSN: | 1785-8860 |
| Appears in Collections: | NĂM 2025 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.