用释义对脓毒症新闻句子进行净化处理

Soma Das, S. Chatterji
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引用次数: 0

摘要

20世纪末互联网的出现,以及21世纪社交媒体的出现,极大地增加了错误信息、虚假信息、宣传和骗局的危害。新的新闻写作方式已经出现,在不使新闻成为假新闻的情况下,巧妙地插入偏见。正确的新闻通常被操纵以使某人、一群人、一个政党或其他因素受益,或者被改变以反映情绪或突出。在呈现给读者之前对这些新闻内容进行净化是一项具有挑战性的任务。本文对英语新闻疑问句进行了研究,并将其定义为脓毒句。我们已经使用机器学习算法识别了无用的句子和它们的无用短语。“净化”是将一个“有缺陷的”句子转化为“纯净的”句子的过程。我们在本文中用释义的方法来说明消毒的过程。该模型能够清除76%的败血症句子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sanitization of Sepsis News Sentences with the help of Paraphrasing
The arrival of the internet in the late twentieth century, followed by social media in the twenty-first century, greatly increased the hazards of misinformation, disinformation, propaganda, and hoaxes. New ways of writing news have emerged to insert bias intelligently without making the news a piece of fake news. The correct news is usually manipulated to benefit a person, a group of individuals, a political party, or other factors, or changed to reflect sentiment or prominence. It is a challenging task to Sanitize such news content before presenting it to the reader. In this paper, we deal with the problematic English news sentences defined as Septic sentences. We have identified the Septic sentences and their Septic phrases using Machine Learning algorithms. Sanitization is the process of converting a Septic sentence into a Pure sentence. We illustrate the process of Sanitization in this paper with the help of paraphrasing. The model is able to Sanitize 76% of Septic sentences.
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