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Memory-Guided Multi-View Multi-Domain Fake News Detection

  • Published:2022 Issue: Volume: Page:1-14
  • ISSN:1041-4347
  • Container-title:IEEE Transactions on Knowledge and Data Engineering
  • language:
  • Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Zhu Yongchun1ORCID,Sheng Qiang1ORCID,Cao Juan1ORCID,Nan Qiong1,Shu Kai2ORCID,Wu Minghui3ORCID,Wang Jindong4ORCID,Zhuang Fuzhen5ORCID

Affiliation:

1. Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China

2. Illinois Institute of Technology, Chicago, USA

3. School of Computer and Computing Science, Zhejiang University City College, Hangzhou, China

4. Microsoft Research Asia

5. Institute of Artificial Intelligence, Beihang University, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Cited by 45 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. EvolveDetector: Towards an evolving fake news detector for emerging events with continual knowledge accumulation and transfer;Information Processing & Management;2025-01

2. Entity-centric multi-domain transformer for improving generalization in fake news detection;Information Processing & Management;2024-09

3. Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. A hierarchical dual-view model for fake news detection guided by discriminative lexicons;International Journal of Machine Learning and Cybernetics;2024-08-23

5. MEFaND: A Multimodel Framework for Early Fake News Detection;IEEE Transactions on Computational Social Systems;2024-08
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