Summary of Automatic News Generation and Fact-checking System Based on Language Processing, by Xirui Peng and Qiming Xu and Zheng Feng and Haopeng Zhao and Lianghao Tan and Yan Zhou and Zecheng Zhang and Chenwei Gong and Yingqiao Zheng
Automatic News Generation and Fact-Checking System Based on Language Processing
by Xirui Peng, Qiming Xu, Zheng Feng, Haopeng Zhao, Lianghao Tan, Yan Zhou, Zecheng Zhang, Chenwei Gong, Yingqiao Zheng
First submitted to arxiv on: 17 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel automatic news generation and fact-checking system leveraging language processing techniques to streamline news production while ensuring the accuracy and reliability of content. The system combines text generation, information extraction, and knowledge graph applications to generate well-structured news articles and prevent the spread of false news. Experimental validation demonstrates the effectiveness of these technologies in enhancing news quality and credibility. Furthermore, the paper explores future directions for automatic news generation and fact-checking systems, emphasizing integration and innovation to drive practical applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research creates a new system that helps make news more efficient and trustworthy by using computers to write articles and check facts. Right now, it takes humans a lot of time and effort to gather information and write news stories. This system can do this faster and better, making sure that what’s published is true and accurate. It uses special computer programs to analyze huge amounts of data, generate text, and check for accuracy. The results show that this system has the potential to make a big difference in the way we get our news. |
Keywords
» Artificial intelligence » Knowledge graph » Text generation
