한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제25권9호
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  • Pages.1275-1278
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  • 2021
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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효율적인 트랜스포머를 이용한 팩트체크 자동화 모델

Automated Fact Checking Model Using Efficient Transfomer

  • Yun, Hee Seung (Department of Computer Engineering, Chung-Ang University) ;
  • Jung, Jason J. (Department of Computer Engineering, Chung-Ang University)
  • 투고 : 2021.07.16
  • 심사 : 2021.07.29
  • 발행 : 2021.09.30
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초록

Nowadays, fake news from newspapers and social media is a serious issue in news credibility. Some of machine learning methods (such as LSTM, logistic regression, and Transformer) has been applied for fact checking. In this paper, we present Transformer-based fact checking model which improves computational efficiency. Locality Sensitive Hashing (LSH) is employed to efficiently compute attention value so that it can reduce the computation time. With LSH, model can group semantically similar words, and compute attention value within the group. The performance of proposed model is 75% for accuracy, 42.9% and 75% for Fl micro score and F1 macro score, respectively.

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과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538).

참고문헌

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