Misinformation Detection and Rectification Based on QA System and Text Similarity with COVID-19
- Title
- Misinformation Detection and Rectification Based on QA System and Text Similarity with COVID-19
- Author
- 조남재
- Keywords
- Misinformation Detection; Fake Information Detection; Qa System; Cosine Similarity; Machine Learning
- Issue Date
- 2021-10
- Publisher
- 한국데이터전략학회
- Citation
- Journal of Information Technology Applications & Management, v. 28, NO. 5, Page. 41-50
- Abstract
- As COVID-19 spread widely, and rapidly, the number of misinformation is also increasing, which WHO has referred to this phenomenon as “Infodemic”. The purpose of this research is to develop detection and rectification of COVID-19 misinformation based on Open-domain QA system and text similarity. 9 testing conditions were used in this model. For open-domain QA system, 6 conditions were applied using three different types of dataset types, scientific, social media, and news, both datasets, and two different methods of choosing the answer, choosing the top answer generated from the QA system and voting from the top three answers generated from QA system. The other 3 conditions were the Closed-Domain QA system with different dataset types. The best results from the testing model were 76% using all datasets with voting from the top 3 answers outperforming by 16% from the closed-domain model.
- URI
- https://www.earticle.net/Article/A406651https://repository.hanyang.ac.kr/handle/20.500.11754/176389
- ISSN
- 1598-6284;2508-1209
- Appears in Collections:
- COLLEGE OF BUSINESS[S](경영대학) > BUSINESS ADMINISTRATION(경영학부) > Articles
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