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Research on Automatic Proofreading Method of Sensitive Information in Content Security

机译:内容安全性敏感信息的自动校对方法研究

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Aiming at the problem of automatic proofreading of sensitive information in mass text content, an automatic proofreading method based on the combination of rule and SVM (Support Vector Machine) is proposed. To classify sensitive information based on important sensitive information provided in the "Newly Prohibited Texts and Cautions in Xinhua News Reports"(newest revision) and related central and online texts.According to the different categories, the paper constructs the classification processing rule base, designs the corresponding rules automatic Processing algorithm, and realizes the sensitive information automatic proofreading, At the same time, using the SVM model to analyze the result of the rule processing with emotion, which greatly reduces the false alarm rate. The test result shows that the recall rate of method is 89.98%, the accuracy rate is 98.31%, and 100,000 + text content is processed per second, which solves the key difficult problems in the practical engineering application.
机译:针对质谱内容中敏感信息的自动校对问题,提出了一种基于规则和SVM(支持向量机)组合的自动校对方法。要基于“新文本禁止和注意事项在新华社的报告”(最新修订版),并提供相关的中央和在线texts.According不同类别的重要敏感信息,敏感信息进行分类,本文构建了分类处理规则库,设计相应的规则自动处理算法,实现了敏感信息自动校对,同时,使用SVM模型以分析与情感规则处理,这大大降低了误报率的结果。测试结果表明,方法的召回率为89.98%,精度率为98.31%,每秒处理100,000 +文本内容,解决了实际工程应用中的关键困难问题。

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