Earticle

초록

영어

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

목차

Abstract
1. INTRODUCTION
2. RELATED WORKS
2.1 Techniques of Artificial Intelligence
2.2 Techniques of Text Mining
3. THE MODEL OF FAKE NEWS CONTENTS IDENTIFICATION
3.1 Architecture of the Proposed Model
3.2 Notion of the Proposed Model
4. THE DESIGN OF FAKE NEWS CONTENTS IDENTIFICATION
5. CONCLUSIONS
Acknowledgement
References

키워드

저자

• Jangmook KANG [ Prof., Dept. of Hacking & Security, Far East Univ., Korea ]
• Sangwon LEE [ Prof., Dept. of Computer & Software Engineering, Wonkwang Univ., Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380