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Technology Convergence (TC)

News Article Identification Methods in Natural Language Processing on Artificial Intelligence & Bigdata

원문정보

초록

영어

This study is designed to determine how to identify misleading news articles based on natural language processing on Artificial Intelligence & Bigdata. A misleading news discrimination system and method on natural language processing is initiated according to an embodiment of this study. The natural language processing-based misleading news identification system, which monitors the misleading vocabulary database, Internet news articles, collects misleading news articles, extracts them from the titles of the collected misleading news articles, and stores them in the misleading vocabulary database. Therefore, the use of the misleading news article identification system and methods in this study does not take much time to judge because only relatively short news titles are morphed analyzed, and the use of a misleading vocabulary database provides an effect on identifying misleading articles that attract readers with exaggerated or suggestive phrases. For the aim of our study, we propose news article identification methods in natural language processing on Artificial Intelligence & Bigdata.

목차

Abstract
1. INTRODUCTION
2. RELATED WORKS
2.1 Bigdata & Artificial Intelligence
2.2 Text Mining
3. THE MODEL OF MISLEADING NEWS DISCRIMINATION SYSTEM
3.1 Architecture of the Proposed System
3.2 Notion of the Proposed System
4. THE DESIGN OF MISLEADING NEWS DISCRIMINATION SYSTEM
5. CONCLUSIONS
ACKNOWLEDGEMENT
REFERENCES

저자정보

  • Jangmook Kang Prof., Dept. of Hacking & Security, Far East Univ., Korea
  • Sangwon Lee Prof., Dept. of Computer & Software Engineering, Wonkwang Univ., Korea

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